Digital anatomical virtual extremities for pre-training physical movement

ABSTRACT

Aspects of the disclosure include methods and systems for pre-action training. In an aspect, a method is presented for constructing a user-controllable image comprising obtaining anatomical and physiological data associated with a body, storing the anatomical and physiological data in a database; and creating the user-controllable image based on the stored anatomical and physiological data. The user-controllable image may be configurable to a user. At least a moveable portion of the user-controllable image may be constructed to move based on input from a user. The user-controllable image may be constructed to enable pre-action training of the user. As such, victims of traumatic brain injury or other neurological setbacks may pre-train their nervous system for use of one or more injured body parts. Additionally, the methods and systems described provide pre-action training control of non-virtual prostheses, exoskeleton body parts, powered orthotic devices, robots or other motile or audiovisual output devices.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of prior U.S. applicationSer. No. 13/841,901, filed Mar. 15, 2013, which claims the benefit under35 U.S.C. § 119(e) of U.S. Provisional Application No. 61/665,221, filedJun. 27, 2012; and this application is a continuation-in-part of priorU.S. application Ser. No. 14/891,789, filed Nov. 17, 2015, which was a371 National of International PCT/US2014/038447, filed May 16, 2014, andwhich claims the benefit under 35 U.S.C. § 119(e) of U.S. ProvisionalApplication No. 61/824,892, filed on May 17, 2013, and also claims thebenefit under 35 U.S.C. § 119(e) of U.S. Provisional Application No.61/830,456, filed on Jun. 3, 2013; and this application claims thebenefit under 35 U.S.C. § 119(e) of U.S. Provisional Application No.62/499,453 filed Jan. 25, 2017, and this application claims the benefitunder 35 U.S.C. § 119(e) of U.S. Provisional Application No. 62/499,977filed Feb. 9, 2017; all of which are incorporated by reference herein.

FIELD OF THE DISCLOSURE

The present disclosure relates to movement therapy apparatus, system,and method.

SUMMARY OF THE DISCLOSURE

Embodiments described herein pertain to the field of user self-teachingpre-action gaming simulations, also known as pre-action training,pre-action exercise, or instantiating kinetic imagery in virtualenvironments. The present disclosure further relates to constructing,configuring, or controlling user controllable images as used inpre-action training. The present disclosure further relates to methodsand systems that provide for user pre-action training control of outputdevices such as non-virtual prostheses, powered orthotic devices,exoskeleton body parts, robots or other motile or audiovisual outputdevices.

The broad medical problem is that the individuals most in need in ofcare e.g., patients, survivors and other health-affected individuals(synonymously “users”) have few, if any, simulations tailored to theirneeds and none in the field. The users' goals may include regaining orimproving processes that enable performing activities of unaffectedliving after, without limitation: neurological injury or conditionresulting from penetrating or non-penetrating insult injury or stress;or physical injury due to invasive or non-invasive causation; orexperiencing psychological or neurochemical disorder. The economicproblem is that the users undergo long-term and costly therapeutic andrehabilitative procedures therefore consuming significant healthcareservices and costs without recourse to heuristic health improvementmethods and systems. The access-to-care problem is that when affected byan injury, condition, or disorder, there are insufficient methods andsystems to activate needed brain processes, or to stimulate, much lessrepeatedly stimulate, without limitation, neurons, neurological supportcells, inter-neuron communications, gray and white matter corticalcircuitry, other brain circuits or communications or tissues or proteinsof the brain or central nervous system. The user's more particularmedical, therapeutic, and rehabilitative care problems are to use themethod and systems at least to improve the neurological, physical, orpsychological conditions noted above.

Further, the broad medical problem is that while physical movementsimulations are extensively in use, individuals most in need in of care,specifically survivors and other health-affected individuals(synonymously “users”) have few if any simulations and correlativephysical activations tailored to their needs and none in said field.Survivors' goals may include regaining or improving processes thatenable performing activities of unaffected living after, withoutlimitation: neurological injury, disorder or condition resulting frompenetrating or non-penetrating insult injury or stress; or physicalinjury due to invasive or non-invasive causation; or experiencingpsychological or neurochemical disorder.

Further, the user's medical therapeutic and rehabilitative care problemsinclude access to diagnoses or measurements or biomarkers of brainprocesses or activations, or determinations of amounts or levels ofbiological substances, without limitation, tau proteins. One solution tothe users' problems in preparing for real-world physical actions is touse methods and system described herein for pre-action control ofuser-controllable images that enable user pre-action training control ofoutput devices such as non-virtual robotic, prosthetic, poweredorthotic, exoskeleton objects, other motile or audiovisual outputdevices.

One objective is to provide a methods and system for enabling the userto instantiate kinetic imagery using simulations i.e. to transition frompersonal mental images or visualizations of physical actions intoinstantiations of simulated physical actions, synonymously, “viewableembodiments of cortical simulations of physical actions.” One technicalproblem therefore is to construct user controllable images that areanatomically realistic, have analogous true range of motion, are usercontrollable to simulate physical actions on any display screen andthereby to provide the user with stimulating virtual alternatives toactual physical action feedback.

A further access-to-care problem is that an affected individual hasinsufficient methods and systems available to activate needed brain andnervous system processes, or to stimulate, much less repeatedlystimulate, without limitation, neurological structures such as neurons,neurological support cells, inter-neuron communications, gray and whitematter cortical circuitry, other brain circuits or communications ortissues or proteins of the brain or central nervous system andcontemporaneously or simultaneously activate by wired or wirelesslymeans at least one device attached to at least one human body part inneed of rehabilitation, therapy or functional correction. The user'smore particular medical, therapeutic, and rehabilitative care problemsare to use methods and system described herein to improve the detrimentsnoted above by controlling a virtual image(s) to simulate physicalmovements and movement and actions and to actuate an attached orunattached body part device such that the device activates or stimulatesone or more body parts. Actuation can be accomplished, for example, bywired or wireless means.

Existing science holds that repeated stimulation of neurologicalreceptors may form “cell assemblies” and that beneficial mathematicalrelationships exist between outcomes of repeated firing ofinterconnected neurological cells and learned behavior. Using themethods and system described herein at least includes and provides forrepeated, self-induced neuronal stimulation and self-teaching, includinginteractive instantiation of kinetic imagery.

The methods and system described herein enable negativelyhealth-affected individuals e.g., the users, synonymously, “plurality ofusers,” to use self-controlled and/or directed pre-action trainingsimulations to stimulate brain structures and processes. Operationally,the user controls virtual body parts that are anatomically realisticwith analogous true range of motion to simulate physical actions,thereby engaging in pre-action gaming simulations. This disclosureenables the user to repeat brain stimulation in part through interactiveinstantiation of kinetic imagery, synonymously, “viewable embodiments ofcortical simulations of physical actions.” The disclosure is directedwithout limitation to individuals affected by stroke, traumatic braininjury, focal dystonias, chronic traumatic encephalopathy, amputees,joint replacement patients, or other conditions in need of physical,occupational or psychological rehabilitation/therapy, withoutlimitation, brain tumors, cerebral palsy, Parkinson's disease, autismspectrum disorders, schizophrenia, phobias, other acquired braininjuries (“ABI”), or other medical deficits, disorders or diseases.

Further operationally, before or without being able to perform physicalaction(s), the user executes inputs (using any input device e.g.,without limitation a computer mouse, touch-screen, head or eye actionsor wireless signals) that control/direct simulated physical actions ofon-screen images. The user's physical method of inputs is physicallynon-corresponding to displayed actions of on-screen images. The inputscontrol virtual body parts whether clothed, skin-covered, or exposed,displayed in any virtual environment. The user inputs may simultaneouslyor sequentially control single or multiple virtual body parts.

Physiologically, the user's challenge is to initiate or improve physicalor related cognitive actions before or without being able to perform orpractice the actions. Using the present methods and system describedherein stimulates survivors' brain and nervous system processes toperform purposeful movements by survivor's instantiating visual imagesof their abstract thoughts regarding purposeful physical movements andmovement and actions. They control realistic virtual extremities thathave analogous true range of motion to simulate physical purposefulmovements and movement and actions (an inside-out process) and by wiredor wireless means actuate at least one attached or unattached physicalbody part device such that the physical body part device activates orstimulates one or more physical body parts. The methods and systemdescribed herein be used for self-teaching, without limitation: a) brainprocesses to enable performing new actions or improve past actions e.g.,to help stroke or traumatic brain injury or chronic traumaticencephalopathy patients; or b) potentiation of brain processes toreplace or supplement damaged neural circuits e.g., helpjoint-replacement patients regain abilities; or c) de-activation ofexisting neuromuscular actions, e.g., to decrease or stop users'uncontrolled muscle contractions as in focal cervical dystonia; or d)de-sensitization of damaged neural circuits e.g., phantom limb or otherpainful body parts; or e) creation of brain processes to supplantdysfunctional/debilitating experiences e.g., suffering from phobias,schizophrenic hallucinations or autism spectrum sensory-actiondisorders.

For individuals with disabled or dysfunctional use of body parts or withpsychological conditions impeding control of actions or relatedcognitive processes, imagined action alone results in imagined feedback.Visualization and imagery alone, e.g., without creating pre-actionsimulations, are only somewhat sufficient for rehabilitating actionplanning or execution or restoration of unaffected physical actions orrelated cognitive processes. The methods and system described hereinprovide video game-like, opportunities so that the user is able totransition from mere visualization to external feedback generation, i.e.to instantiate abstract mental representations of physical actions intoactual visual displays of simulated physical actions, synonymously,“viewable embodiments of cortical simulations of physical actions.”

Existing theories hold that repeated stimulation of neurologicalreceptors may form “cell assemblies” and that there are beneficialmathematical relationships between outcomes of repeated firing ofinterconnected neurological cells and learned behavior. Using themethods and system described herein at least includes and provides forrepeated, self-induced neurological stimulation and self-teaching,including interactive instantiation of kinetic imagery.

Using the present disclosure, the user may attempt to create simulatedphysical actions and may succeed in doing so. Consequently, the user'splanning processes for anticipated and intended physical actions andrelated cognitive processes are activated. This activation may befollowed by controlling and/or directing desired, purposeful, simulatedactions. Basically, the user anticipates or intends to originate orotherwise cause simulated physical actions and knows the meaning of suchactions. Using the methods and system described herein, which includeutilizing or creating instantiated kinetic imagery feedback, may help toillustrate and reinforce what the user planned to do and actually did.Repetition makes it possible to do that better.

The following presents a simplified summary of one or more aspects ofthe present disclosure in order to provide a basic understanding of suchaspects. This summary is not an extensive overview of all contemplatedaspects, and is intended neither to identify key or critical elements ofall aspects nor to delineate the scope of any or all aspects. Its solepurpose is to present some concepts of one or more aspects in asimplified form as a prelude to the more detailed description that ispresented later.

The one or more users of the present methods and system described hereinare able to transition from conscious imagery/visualization, in effectabstract mental processes, to real visuomotor feedback. Accordingly, forthe affected conditions, injuries, disorders or experiences, or for anyuser who is challenged, the methods and system described herein enableinstantiation of kinetic imagery, i.e. “viewable embodiments of corticalsimulations of physical actions” resulting in feedback that is next-bestto actual physical action feedback for self-teaching, self-re-learning,self-re-exercising physical actions or skills or related cognitiveprocesses or self-therapy-rehabilitation.

Aspects of the present disclosure relate to methods and systems forinstantiating kinetic imagery. More particularly, the methods and systemdescribed herein includes instantiating kinetic imagery by a usercontrolling virtual body parts alone or in conjunction with virtualobjects. In an aspect, a user may engage in one or more self-teachingvirtual training games, i.e. Pre-action Exercise Games (“PEGs”). PEGsprovide users with stimulating substitutes for actual physical actionfeedback. The feedback fosters stimulation aspects of any user's brainpreviously compromised due to any of the conditions or disorders listedin this disclosure or other conditions that may be within the scope ofthis disclosure. PEGs provide simulated physical action feedback fromuser controlled/directed virtual body parts corresponding ornon-corresponding to the user's body part(s) that may have sufferedreduced or lost functionality. The user, controlling virtual worldactions, is engaged in virtual training for real-world actions. In anadditional aspect, PEGs provide a user with a neuronal workout thatstimulates without limitation neuronal recruitment, synaptogenesis orbrain plasticity, functions or processes.

PEGs provide a link between kinetic visualization/imagery and useroriginated-controlled/directed simulated physical actions. Visualizationand imagery of physical action is an integral step in motor planning,physical performance or reacquisition of purposeful physical actionsthat have been compromised. The methods and systems described hereinimplement kinetic imagery by providing each user with means to ‘act out’or otherwise control virtual body parts so that the simulated actions ofbody parts represent instantiated, real visual displays of a user'sabstract processes of visualization/imagery.

The present disclosure further relates to constructing, configuring,and/or controlling user controllable images, such as those used inpre-action training. According to aspects of the present disclosure,presented is a method of constructing a user-controllable image, whichincludes obtaining anatomical and physiological data associated with amodel of the body, storing the data in a database, and creating theuser-controllable image based on the body model data, wherein theuser-controllable image may be configurable to a user, wherein at leasta moveable portion of the user-controllable image is constructed to movebased on input controls from a user, and wherein the user-controllableimage is constructed so as to enable pre-action self-training by a user.In an additional aspect, demonstrative actions of the user-controllableimage or any image(s) can be generated by using motion capture or othertechnologies. In an additional aspect, motion capture or othertechnologies can likewise be used to construct and/or configure a usercontrollable image.

In an additional aspect, presented herein is a method of configuring auser-controllable image to a user, which includes obtaining at least onedefault parameter associated with the user-controllable image, obtainingat least one user parameter associated with a user body, comparing theat least one default parameter and the at least one user parameter,constructing a user-configured, user-controllable image by adjusting oneor more of the at least one default parameter where the at least oneuser parameter differs from the at least one default parameter, whereinthe user-configured, user-controllable image is configured so as toenable pre-action self-training by a user, and providing theuser-configured, user-controllable image to the user for pre-actiontraining. In an additional aspect, motion capture or other technologiescan likewise be used to configure a user-controllable image (“UCI”).

The present disclosure further provides an example method of controllinga user-controllable image, which includes providing a virtual body partto a user, wherein the user-controllable image comprises the virtualbody part, receiving a selection input or multiple selection inputs fromthe user, wherein the selection input(s) is associated with at least aportion of one or more virtual body parts, receiving an action inputfrom the user, and displaying an action of the at least a portion of thevirtual body part based on the action input, wherein the displayedaction is physically non-corresponding to the action input and whereinthe selection input(s) and action input(s) are at least a part ofpre-action self-training by a user. In addition, the methods and systemdescribed herein contemplate use of, without limitation, apparatuses,computers, computer readable media, hand-held devices, computer programproducts, internet accessibility, multi-user use and means forperforming these the example methods.

The present disclosure further relates to methods and systems thatprovide for user pre-action control of output devices such asnon-virtual prostheses, exoskeleton body parts, powered orthoticsdevices, robots, or other motile or audiovisual output devices,synonymously, “at least one non-virtual object.” This disclosureprovides an example method for controlling a UCI representing the atleast one non-virtual object. It includes providing a virtualrepresentation of a non-virtual object to a user, wherein therepresentation of a non-virtual object receives a selection input(s)from the user, wherein the selection input is associated with at least aportion of the non-virtual object, wherein receiving an action(s) inputfrom the user, and displaying, approximately simultaneously, the virtualaction and a physical action of the at least a portion of thenon-virtual object and based on the action input, wherein the virtualand physical actions are physically non-corresponding to the actioninput and wherein the selection input and action input are at least apart of pre-action training a user to use a non-virtual object.

Further aspects of the methods and system described herein relate tousing pre-movement and action exercise games, or PEGs, for medicaldiagnostic purposes or measuring brain processes and biologicalsubstances, or biomarkers, to improve PEGs. In such further aspects ahealth-affected user, using PEGs, simultaneously has brain processes andbiological substances assessed or measured, then compared to a baselineof control non-health-affected users who have used or are using PEGs.

Further aspects of the methods and system described herein relate tohealthcare or research professionals learning or researching “what-ifs”relating to any of the conditions to which this disclosure isapplicable.

The methods and system described herein may be non-invasive, solo videogame-like, heuristic, economical and useable on any computer or otherdigital device, practically anywhere and at any time. The methods andsystem described herein have the potential to leverage users'rehabilitation or therapists' productivity to high levels. The methodsand system described herein are well-suited to hands-on or telemedicinehealthcare services.

In one embodiment of the present invention, a system for improvement ofphysical motor control of affected human extremities and relatedcognitive and nervous system processes includes a computer device havingan input device and a display device each disposed in communication withthe computer device. The computer device is configured to display to auser a virtual body part that represents a corresponding body part ofthe user requiring improvement. The virtual body part(s) optionallyincludes one or more selectable body part portions. The virtual bodypart or the selectable body part portion(s) is (are) shown in a firstposition or configuration on the display device. The computer devicereceives one or more user inputs that cause the virtual body part tomove in a user-directed motion or a predefined motion. The computerdevice displays the predefined or user-directed motion of the virtualbody part (and/or of the selectable body part portion) to a secondposition or configuration based on the user input. The user repeats theuser input as necessary to cause improvement of physical motor controlof the corresponding body part of the user and related cognitive andnervous system processes improvement.

In another embodiment of the system, the user input includes one or bothof a selection input associated with the selectable body part and amovement and action input indicating the virtual movement in virtual 3Dspace of the body part.

In another embodiment of the system, the computer device is furtherconfigured to provide to the user an instruction to perform a taskselected of moving the virtual body part in virtual 3D space, changingthe position of the at least one selectable body part to a secondposition in virtual 3D space, moving an object in virtual 3D space,grasping a virtual object, touching a virtual object, aligning thevirtual body part with a virtual object, positioning the virtual bodypart relative to a virtual reference point, using the virtual body partto select a virtual object, releasing an object, or rotating the virtualbody part in virtual 3D space.

In another embodiment of the system, the computer device is furtherconfigured to provide to the user an instruction to perform a task ofaligning the virtual body part with a displayed reference point,selecting one object among a plurality of displayed objects, or movingthe at least one selectable body part to a displayed target.

In another embodiment of the system, the input device is configured todetect a biomarker or neurological signal of the user, correlate thebiomarker or neurological signal to a movement and action associatedwith the virtual body part, and display to the user a virtualmanifestation of the movement and action based on the biomarker orneurological signal.

In another embodiment of the system, the input device includes a usermovement and action recognizing component configured to recognize amovement and action of the user.

In another embodiment of the system, the computer device is configuredto display an indicia on the virtual body part or a portion thereof inresponse to the user input.

In another embodiment, the system includes a tangible body part devicedisposed in communication with the computer device, where the computerdevice is configured to output a control or actuation signal to thetangible body part device based on user input. In one embodiment, thefeedback device may be a tangible body part device disposed incommunication with the computer device, where the tangible body partdevice may be actuated by a sound signal from the computer device.

In another embodiment, the system includes a feedback device disposed incommunication with the computer device, wherein the feedback deviceprovides feedback to the user based on the user input, where thefeedback to the user is without limitation a sound or electrical signalcoupled to or communicating with a muscle or nerve of the user, tactilefeedback, visual feedback, audio feedback, or an electrical or soundsignal configured to control a tangible body part device disposed incommunication with the computer device.

In an embodiment where the feedback is an electrical or sound signalconfigured to control a body part device, the tangible body part deviceis connected to the user. For example, the tangible body part device isoperationally connected to the user. In another embodiment, the tangiblebody part device is not connected to the user. In another embodiment,the electrical or sound signal contemporaneously causes the body partdevice to substantially perform the movement of the virtual body partbased on the user input.

In another embodiment of the system, the input device is configured toobtain a user measurement and compare the user measurement to a controlvalue, where the user measurement is a neurological signal, a biologicalsubstance measurement, and/or a biomarker measurement.

In another embodiment of the system, the computer device is furtherconfigured to display to the user a demonstrative movement and action ofthe virtual body part, indicate to the user at least one virtual bodypart used to perform the demonstrative movement and action, instruct theuser to mimic the demonstrative movement and action by entering at leastone user selection, and receive the one user selection where the userselection(s) is (are) associated with the virtual body part used toperform the demonstrative movement and action.

In one embodiment, the viewable embodiments of cortical simulations ofphysical actions may be constructed as specialized computer digitalmultimedia packages capable of receiving and processing digital inputsand generating visual and/or audio outputs for display and/orpresentation to a user via a digital device. In one aspect, the digitalmultimedia packages may be digital anatomical virtual extremities.

In one embodiment, methods and system described herein may include anexternal mechanical device configured to receive one or more controlsignals from computer device corresponding to the virtual movement ofthe digital multimedia packages being manipulated by the user. Theexternal mechanical device may be attached to the user and may processthe control signals to prompt movement of one or more body parts, whichmay include the user's affected body part.

To the accomplishment of the foregoing and related ends, the one or moreaspects comprise the features hereinafter fully described andparticularly pointed out in the claims. The detailed description of themethods and system described herein and the annexed drawings set forthin detail certain illustrative features of the one or more aspects.These features are indicative, however, of but a few of the various waysin which the principles of various aspects may be employed, and thisdescription is intended to include all such aspects and theirequivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system-level component diagram illustrating a system forpre-action training according to aspects of the present disclosure.

FIG. 2 is a component block diagram of aspects of a computer device forpre-action training according to aspects of the present disclosure.

FIG. 3 is a component block diagram of aspects of a UCI constructingdevice according to aspects of the present disclosure.

FIG. 4 is a component block diagram of aspects of a computer deviceaccording to aspects of the present disclosure.

FIG. 5 is a flow diagram illustrating aspects of an example method ofconstructing a UCI according to the present disclosure.

FIG. 6 is a flow diagram illustrating aspects of an example method ofconfiguring a UCI to a user according to the present disclosure.

FIG. 7 is a flow diagram illustrating aspects of an example method ofproviding pre-action training activities to a user according to thepresent disclosure.

FIG. 8 is a flow diagram illustrating aspects of an example method ofinstantiating a virtual movement and reinitiating neurologicalfunctionality according to the present disclosure

FIG. 9 is a component diagram illustrating an example grouping ofelectrical components for creating a UCI according to the presentdisclosure.

FIG. 10 is a component diagram illustrating an example grouping ofelectrical components for configuring a UCI to a user according to thepresent disclosure.

FIG. 11 is a component diagram illustrating an example grouping ofelectrical components for providing pre-action training activities to auser according to the present disclosure.

FIG. 12 is a component diagram illustrating an example grouping ofelectrical components for instantiating kinetic imagery, i.e.embodiments of cortical simulation and reinitiating neurologicalfunctionality according to the present disclosure.

FIG. 13 is a representative drawing a non-virtual robot, poweredorthotics device, prosthesis, or exoskeleton body part according to thepresent disclosure.

FIG. 14 is a representative wiring diagram of a non-virtual robot,powered orthotics device, prosthesis, or exoskeleton body part accordingto the present disclosure.

FIG. 15 is a representative wiring diagram of a non-virtual robotpowered orthotics device prosthesis, or exoskeleton body part accordingto the present disclosure.

FIG. 16 is a block diagram illustrating a machine in the example form ofa computer system according to an example aspect of the presentdisclosure.

FIG. 17A illustrates a virtual body part displayed by a display deviceand showing the virtual body part in a first configuration.

FIG. 17B illustrates the virtual body part of FIG. 17A shown in a secondconfiguration.

FIG. 18 illustrates an example of a virtual body part performing thetask of grasping a coffee mug.

FIG. 19 illustrates an example of a pre-movement and action exercisegame in which the user uses a virtual body part to select and moveblocks.

FIGS. 20-23 illustrate an example operation of the system and method ofthe disclosure.

FIG. 24 illustrates a flow chart of one embodiment of a method of thedisclosure.

DETAILED DESCRIPTION OF THE INVENTION

Purposeful and reflexive physical actions of body parts are proximallyderived from neuronal signaling (spinal cord outputs) to muscles.However, pre-action planning for purposeful actions is derived fromneuronal signaling (outputs) of brain structures or processes initiatingthe neural signaling of the spinal cord. Brain communications areessential to initiating purposeful new physical actions or to regainingability to perform the physical actions or related cognitive processesor to correct physical, neurological or psychological actions associatedwith disorders or conditions.

The damaged brain, no less than other damaged body parts, requirestherapy or rehabilitation. No known technologies, other than thosedescribed in this disclosure, are directed to pre-action planning,training, or exercises in virtual environments. None are known to enableusers to instantiate kinetic imageries of physical actions in anyvirtual environment i.e. to originate or create viewable embodiments ofcortical simulations of physical actions.

Acquired brain injury (“ABI”), including stroke, chronic traumaticencephalopathy, and traumatic brain injury (“TBI”) survivors, or withoutlimitation, individuals affected by any condition, disorder, orexperience noted in this disclosure, may sustain impaired or eradicateduse of one or more body parts. The result is formation of mild to severebarriers to physically controlling one's actions. The barriers existdespite, in many instances, body parts being totally or somewhatuninjured. For ABI survivors it is fair to say that except for the braininjury (and consequential atrophy) chronic physical action deficitswould not require rehabilitation. To address the deficits ABI survivorsundergo long-term and costly therapeutic and rehabilitative procedures.These are major healthcare services or cost problems. Epidemiologically,and by way of example, the combined, annual incidence of ABI, stroke andtraumatic brain injury (“TBI”) alone, in the United States leaves 2.5million survivors annually. A broader category, neurotrauma (penetratingand non-penetrating), including primary brain tumor, focal dystonias,limb apraxia/ataxia, cerebral palsy and amputations, affects more than12 million U.S. civilians and approximately 200,000-400,000 combatveterans. Assuming that the incidence of ABI/TBI alone is generallyuniform worldwide, by extrapolation the total number of ABI/TBIsurvivors worldwide would exceed 50 million individuals. The totalnumber of neurotrauma survivors worldwide would therefore exceed 275million individuals, which represents a number approximating the entireU.S. population.

Conventional rehabilitation/therapies for treating ABIs are primarilyphysical in nature involving assisted and independent efforts to restoresurvivors to being able to make unaffected physical actions. Physicaland occupational therapy actions are characterized in that the movementsof survivors' body parts correspond to intended unaffected movements.That recovery process is predominantly outside-in. In contrast, theprocesses described herein are inside-out. Methods and systems forpre-action training target brain structures or processes, i.e. aprincipal pathological site for ABI/TBI survivors or other affectedindividuals.

Making corresponding physical training movements are variably effective,but difficult or impossible for those recovering from ABI/TBI or otherconditions or disorders noted above. From the survivors' perspective,the challenge and question are how to practice physical actions or trainto move without being able to move. ABI/TBI survivors are left withdisconnections between, on one hand, intact, and in many cases,initially uninjured body parts and on the other hand, dysfunctionalbrain processes required for planning the movements of such body parts.In some cases, patients' and survivors' difficulties are magnified dueto the individual's non-awareness of the existence of an unusable bodypart. One challenge for ABI/TBI survivors is to regain the use of bodyparts. That challenge is addressed by using the methods and systemherein to control virtual body parts so as to make simulated actionsbefore, during, after or adjunctive to utilizing physical or assistiverehabilitation or therapeutic methods that use corresponding physicalactions by such body parts. Thus to regain full and expeditious controlof using ABI/TBI-affected body parts, the present methods and systemsdescribed herein may be utilized for providing pre-action training.

Conventionally for ABI, at least one of three therapies is used. Theyare, motor imagery; mirror therapy; and action-observation therapy.Motor imagery involves imagining motor controls and attempting tophysically exercise the resulting imagery. Mirror therapy has been usedfor amputees experiencing phantom limb pain. It involves using an intactbody part to make physical actions reflected in a physical mirror. Themirrored actions appear to be made by the contralateral (amputated) bodypart. The patient's observation of the actions has been shown todecrease or terminate phantom limb pain. Action-observation therapy istheoretically mirror neuron based and involves viewing physical actionsfollowed by the patient's efforts to match i.e. imitate the observedactions. None of the foregoing therapies are video game-like in terms ofinteractivity, immersion, scope, versatility, heuristic teachingmethodology, economy, or entertainment. None enable patients toinstantiate kinetic imagery Unlike current therapies or rehabilitation,the disclosed techniques enable individuals, in a video game-likevirtual environment, to independently make inputs that interactivelycontrol virtual body parts. By personally causing simulated physicalactions to be displayed, the individuals produce real visuomotor(visuoaction) feedback from the simulated actions and induce new oraugmented brain processes.

Humans excel at creating mental imagery. Imagery and simulation occurwhile conscious or during dreams. Conscious, imagined actions precedeand are fundamental to making purposeful physical actions. Makingrepeated physical actions, accompanied by feedback acquired from suchactions, results in improved action skills. For unaffected individuals,the process of creating productive feedback evolves from mentalabstractions to making actual physical actions in the real world andreceiving feedback via sensory-action return signals. That process isvariably unavailable or impossible for many individuals affected by theaforementioned conditions. However, for the affected individuals thedisclosed methods and system may be used to create productive actionfeedback directed to improving action planning or regaining physicalactions for daily living.

Various aspects relate to methods and systems for pre-action training,also disclosed as pre-action training for ABI/TBI survivors. The termABI/TBI survivors as used in this disclosure includes without limitationother conditions and disorders described in this disclosure and othersto which pre-action training may be useful. More particularly, themethods and system herein are for pre-action training by ABI/TBIsurvivors using virtual body parts. In an aspect, a user, who may be anABI/TBI survivor, may engage in one or more Pre-Action Exercise Games(“PEGs”). PEGs provide ABI/TBI survivors with brain stimulatingsubstitutes for actual physical-action feedback. The PEGs feedbackfosters the user's restoration of pre-action brain processing, such asthose parts of the brain previously compromised due to the ABI/TBI. PEGsprovide simulated physical-action feedback from user-originated physicalsimulations via controlled/directed, virtual body parts corresponding toat least the user's body parts that suffered reduced or lostfunctionality as the result of ABI or TBI. Such survivorcontrolled/directed, virtual body parts are caused by the user tosimulate physical actions thereby executing virtual-world actions aspre-action training for real world actions. In an additional aspect,PEGs provide the ABI/TBI survivor with a pre-action training workoutthat stimulates, without limitation, neuronal recruitment, inter-neuroncommunication, neurogenesu(is), synaptogenesis, and brain plasticity.

PEGs provide a link between kinetic imagery/visualization anduser-originated simulated physical actions. Imagery/visualization ofphysical actions is integral to action planning, physical performance,and reacquisition of physical actions or skills. The methods and systemsdescribed herein support kinetic visualization and imagery by providingeach user with means to ‘act out’ or otherwise control virtual bodyparts so that the body parts represent real visual instantiations of auser's abstract processes of imagery/visualization.

PEGs are without limitation exercises used in pre-actioncontrol/direction of virtual body parts to simulate physical actionintentions and at least to receive feedback for neuro-rehabilitation ofaction-planning processes.

According to aspects of the present disclosure, inter-movement andaction with virtual body parts, links any user's cognition,visualization, or imagery to virtual action feedback. Furthermore, themethods and systems described herein can engage ABI/TBI survivors toself-teach action planning for purposeful physical actions.

According to aspects of the present disclosure, an ABI/TBI survivor maytarget and help overcome her/his action deficits by making inputs to asystem that displays a user-controllable virtual body part, therebydirecting and causing simulated actions of a moveable region of thevirtual body part based on the inputs, viewing feedback from suchsimulated actions and building new and/or re-building impairedneurological or brain processes.

According to the present disclosure, any user may control and directvirtual body part(s) to display simulated, human physical actions with avirtual full range of motion. The user may control a virtual body partto speed up, slow down, stop or make any combination of the actions orgradations of same. System displays of virtual body part movements andactions may be idiosyncratic representations of each survivor's inputcontrols and direction. In effect, the user's virtual body part controlprocess stimulates cognitive processes and pre-movement and pre-actiontraining for real action processes.

In an aspect, a computer device may control and display virtual movementof the virtual body part and may transmit one or more signals to a(tangible) body part device, which may stimulate one or more body partsof the user to move, for example, in a way that may correspond to themovement of the virtual body part. In some examples, the body partdevice may initiate body part movement by stimulating one or morereceptors or triggers of the user's neurological system, which may inturn cause movement of the muscles, tendons, tissue, or any other partof the user's body.

Furthermore, the methods and systems described herein differ from moderngaming systems like Wii™ and Kinect™ that are being used for physicaland occupational rehabilitation. The systems require their users to makeactual physical actions that are then displayed in virtual environments.Therefore, by design, Wii™ and Kinect™ users make actual physicalactions that correspond to displayed actions. Conversely, the methodsand systems described herein eliminate the requirement of userperformance of corresponding physical actions to what are then displayedas simulated physical actions. For example, a user of the methods andsystem herein can make small or limited non-corresponding eye and/orhead gestures carried by webcam signals, and wirelessly transmit brainsignals, to control the simulated actions of virtual body parts. In butone example, any user's input signals by eye controls (alone) can directa virtual shoulder to move an arm 90 degrees away from the virtual body.Accordingly, a user's input signaling processes associated with themethods and system herein are non-corresponding to the simulatedmovement and actions of the virtual body part. That is to say a user'sphysical method of input, e.g., movement of a wired or wireless mouse,or eye or head movements or transmission of a wired or wireless brainsignal from the user, does not correspond to the simulated actions ofthe virtual body parts of the present disclosure.

The inputs (controls and directions) described herein are dissociatedfrom displayed virtual-image actions and allow ABI/TBI survivors tocause simulated physical actions (action processes) before and withoutperforming real physical training action processes. Each user's inputsaccording to the present disclosure are not physical-training actionmovements of the desired drill or skill. Rather, the present methods andsystems target without limitation neuronal systems, brain structures,gray and white matter circuitry, neurogenesis, synaptogenesis,myelination, brain plasticity, and cognitive processes, not anyparticular physical-action inputs or outputs.

Physical training participation, due to its repetitive aspects, can betedious and hindered by boredom. Participation in physical training isalso fraught with new injury or aggravating old injury. PEGs provideentertaining, rewarding, and immersive features, including game sequenceactions that result from a user's successful control, direction, andmanipulation of virtual body parts and objects that also direct outputdevices such as non-virtual robots, powered orthotic device, prosthesesor exoskeleton body parts.

For example, in terms of non-limiting and non-exclusive variations ofresearch and investigation, as well as practical application, monitoringbrain activity can enhance PEGs' pre-action training value. ABI/TBIsurvivors' brain activities or processes can be measured through anybrain imaging technology or by analyzing blood and/or other body fluids,or biomarkers, or other substances for particular bio-chemicals,markers, and/or compounds related to without limitation overall braincortical, or cognitive activity. Biomarkers include but are not limitedto pulse rate, blood pressure, respiration rate, perspiration, bodytemperature, and eye dilation. Typically, biochemical levels andneurological signals may be measured or monitored to detect a spike orchange in the level in response to an event or stress.

ABI/TBI survivors' baseline brain activities or processes could bedetermined before, during, and after PEGs training to measure changesaccompanying PEGs training. For example, a signal peak, amplitude value,numerical value, concentration, timing of a signal, length of a signal,and other signal characteristics can be observed and compared withbaseline values, threshold values, or ratios. Based on theseobservations, one may draw conclusions regarding the progress of theindividual in restoring or improving a deficit or diagnose conditions,such as TBI, in a subject. Additionally, ABI/TBI survivors' brainactivities or processes can be compared to non-ABI/TBI affectedindividuals undergoing or who underwent PEGs training activities todetermine whether PEGs training is stimulating the same or similaraffected parts of the ABI/TBI survivors' brains as are stimulated in thenon-ABI/TBI affected individuals' brains. PEGs can be adjustedaccordingly to enhance the brain activity or processes in the identifiedbrain structures, processes or circuitry of the ABI/TBI survivors tomatch brain activities (including substance quantities, levels, and thelike) of non-affected individuals' brain structures, processes orcircuitry accompanying PEGs training. Other non-limiting andnon-exclusive variations on the process are discussed below.

PEGs can also be used as a non-invasive diagnostic tool. Some ABI/TBIsurvivors suffer mild brain injury, however current diagnostics arelimited, comprising mostly subjective tests and some technical means.Additionally, while moderate to severe ABI/TBI is detectable throughchanges in brain morphology by CT-scans, MRI or other imagingtechnologies, mild ABI/TBI is difficult to detect or diagnose. Anysurvivor, who does not show severe or moderate TBI, could also beintroduced to playing PEGs to monitor for mild ABI/TBI. Potentiallymildly affected patients would play PEGs, and her/his brain activitieswould be compared to unaffected individuals' baseline brain activitiesto determine the comparative state or extent of mild injury or thepossibility of unlikely or no detectable injury. PEGs may be used forassessing other levels of ABI/TBI, either solo or in conjunction withother methods or devices.

Various aspects are now described with reference to the drawings. In thefollowing description, for purposes of explanation, numerous specificdetails are set forth in order to provide a thorough understanding ofone or more aspects. It may be evident however, that such aspect(s) maybe practiced without these specific details.

Turning to FIG. 1, a system 100 is presented for presentation andmanipulation of a virtual body part as means for pre-action(synonymously pre-movement) training a user. In an aspect, system 100may include a computer device 102, an input device 104, a display device106, and a user measurement device 108. Additionally, system 100 mayoptionally include an body part device 128 and/or a feedback device 130.According to an aspect, computer device 102 may be configured to receiveand process one or more user inputs 110 from input device 104, one ormore user characteristics 112 from user measurement device 108, and mayalso be configured to generate and transmit one or more display controlmessages 114 to display device 106. In addition, computer device 102 maybe configured to execute manipulation of a displayed virtual body partbased on at least the inputs 104 of user 120.

Furthermore, computer device 102 may include a processing engine 116,which may be configured to receive, process, and transmit signalsassociated with display, control, and/or behavior of a virtual bodypart. Additionally, computer device 102 may include a memory 118, whichmay be configured to store user characteristics (such as neurological orchemical characteristic values observed and/or measured from a user 120)and/or instructions for executing one or more PEGs.

In an aspect, input device 104 may be configured to receive one or morephysical or non-physical inputs 122 from a user 120 and process andforward the processed physical inputs to computer device 102 as inputs110. In an aspect, input device 104 may be any means of receiving directphysical input from a user 120, such as, but not limited to a keyboard,mouse, touch pad, touch screen, smart phone, laptop, computer or genericcomputing device, a microphone, an input device that senses inputwithout intervention of the user, etc. In one example, input device 104detects commands spoken by user 120. Alternatively, or additionally,input device 104 may be a device configured to generate input 110 byrecognizing and processing one or more user actions at user actionrecognizing component 124, such as a movement detector, eyewear (e.g.,Google glass), or headgear. For example, in an aspect, user actionrecognizing component 124 may be configured to recognize user inputsvia, by non-limiting example, eye action, nominal physical action ofhands or other body parts, blinking, nodding, and/or by detecting andmonitoring neurological signals generated by the user's body. Forexample, user action recognizing component 124 may include a componentcapable of reading instructions signaled in the brain, spinal cord, orany other neurological circuit or tissue of the user 120.

Furthermore, display device 106 may be configured to display a virtualbody part and actions of the virtual body part. In an aspect, displaydevice 106 may display the virtual body part visually on a screen ordisplay, such as, but not limited to, a computer monitor, projector,television, or the like). Alternatively, or additionally, external bodypart device 128 may receive one or more external body part controlsignals 132, which may cause the external body part device 128 to move,for example, by mechanical means. In an aspect, external body partdevice 128 may be, but is not limited to being, output devices such as arobotic arm, shoulder, prosthetic limb, a powered orthotic device,glove, sleeve, or sock, or the like. In some examples, the external bodypart device 128 may stand alone and be placed in a location viewable bythe user 120. Additionally, the external body part device may beattached to the user 120, which may allow the user to witness more “trueto life” actions associated with his or her physical inputs 122.

In an additional or alternative aspect, body part device 128 may beconfigured to receive one or more control signals from computer device102 corresponding to the virtual movement of the virtual body part beingmanipulated by user 120. Based on the one or more control signals, thebody part device 128 may process the control signals and stimulate oneor more target body parts 150 of the user 120 (or of a non-user (notshown)) to prompt movement of one or more body parts, which may includetarget body part 150.

In yet another aspect, system 100 may include a feedback device 130configured to provide feedback 136 to the user 120. In an aspect,feedback device 130 may receive one or more feedback control messages134 related to the feedback device from computer device 102, which maygovern the movement and action and behavior of the feedback device 130.In an aspect, feedback 136 may include, but is not limited to, forcefeedback, pneumatic feedback, auditory or visual feedback, non-forcefeedback, or any other form of feedback that may indicate an output ofcomputer device 102 related to pre-action training. For non-limitingexample, feedback device 130 may be a mechanical device that a user mayattach to his or her hand or arm that may provide force feedback to theuser's hand or arm in order to bend the user's wrist. In such anexample, this bending may occur where the user selects a virtual wriston display device 106 and moves the virtual wrist up and down (or in anydirection) by moving input device 104. Based on this input, processingengine 116 may generate and transmit a feedback control message 136 tothe feedback device 130—here, the mechanical device—which may provide aforce to the user's wrist to move it substantially in unison with theaction of the virtual image, which may be displayed on display device106 concurrently.

As another non-limiting example, feedback device 130 can be a hapticdevice (e.g., a haptic mouse, belt, vibration alert, electroactivepolymer, piezoelectric wave actuator, electrostatic or subsonic audiowave actuation, or electrovibration) or an electrical feedback device incontact with the user (e.g., an electrode, conductive mat, conductivegarment, etc.).

In an additional aspect, system 100 may include a user measurementdevice 108, which may be configured to measure one or more usercharacteristic values before, during, and/or after engaging inpre-action training activities. In some examples, user characteristicvalues may include without limitation neurological or chemical data,pulse, blood pressure, body temperature, pupillary dilation,perspiration, respiration rate, or any other measurable characteristicor physical parameter of an animal, which may include a human being. Inan aspect, user measurement device may utilize imaging technology tomeasure these user characteristics, and such imaging technologies mayinclude, without limitation, Magnetic Resonance Imaging (MRI),Functional Magnetic Resonance Imaging (fMRI), Computed Tomography (CT),Positron Emission Tomography (PET), Electroencephalography (EEG),Magnetoencephalography (MEG), Near-infrared spectroscopy (NIRS), andHigh Density Fiber Tracking (HDFT).

In a further aspect, user measurement device 108 may send the measureduser characteristic data 112 to computer device 102 upon measurement.There, the user characteristic data may be (a) stored in memory 118 forlater use or (b) fed to processing engine 116 as feedback data thatprocessing engine 116 may utilize to alter an ongoing pre-actiontraining activity, such as an ongoing PEG, or may be used to diagnose amedical condition. Alternatively, where the user characteristic data isstored in memory, such data may be used to tailor future pre-actiontraining activities to the user's individual characteristics or currentskill level or to track the progress of a user over time, or to improvePEGs.

Turning to FIG. 2, an illustration of components comprising computerdevice 102 (FIG. 1) is shown. In operation, computer device 102 maypresent an initial or default virtual body part to a user, for example,when the user, trainer, coach, therapist, or any other type of userinitially boots up computer device 102, selects a PEG 226 for pre-actiontraining activities, or the like. To display this default virtual bodypart, virtual body part manager 204 may query memory 118 for defaultparameters 224 of a set of physical characteristic values 220 storedthereon and may process and display the default virtual body part bysending, for example, one or more display control signals to a display.In addition, once the user begins a pre-action training session,computer device 102 may receive inputs from the user, such as, but notlimited to, selection inputs and action inputs. Based on these one ormore inputs and pre-stored and executable PEGs 226 located in memory118, the computer device may present a selectable, movable, andotherwise interactive virtual body part with which a user may engage topartake in pre-action training activities.

As previously outlined, computer device 102 may include processingengine 116 and memory 118—the operation and composition of which will beexplained in reference to FIG. 2. First, processing engine 116 may beconfigured to process one or more input signals and transmit theprocessed signals to a display device for presentation of auser-controllable image, such as a virtual body part, to a user. Forpurposes of the present description, a user-controllable image (UCI) maybe all or part of a virtual body part or object controllable by userinput to simulate physical actions, wherein these physical actions arenon-corresponding to the user's physical movements and actions ingenerating the user input. Examples of UCIs described herein maycomprise a virtual body part or virtual body parts, but the scope ofsuch examples should not be limited thereto.

In an aspect, processing engine 116 may include a PEG executioncomponent 202, which may process user inputs to generate display controlmessages according to instructions related to one or more PEGs. In anon-limiting example, a user may select a particular PEG to play and asa result, PEG execution component 202 may load the PEG instructions fromPEGs 226 stored in memory 118. After loading the PEG, the PEG executioncomponent 202 may generate one or more display control messages fortransmission to a display device based on the PEG and any input messagesreceived from an input device. Furthermore, in an aspect, PEG executioncomponent 202 may be configured to alter one or more PEGs based onfeedback from a user measurement device. In a non-limiting example, PEGexecution component 202 may receive an indication that a user'sneurological system is stronger than in the past and may make playing aparticular PEG more difficult to maximize further neurologicalimprovement.

In an additional aspect, processing engine 116 may include a virtualbody part manager 204, which may be configured to virtually constructand manage action of a virtual body part that computer device 102 maygenerate for display on a display device. Furthermore, for purposes ofthe present description, the term “display device” may correspond todisplay device 106, body part device 128, feedback device 130, or anyother device or means capable of producing output corresponding to anaction, and/or status of a virtual body part, including output resultingfrom user input during pre-action training activities.

In an aspect, virtual body part manager 204 may include a selectioninput managing component 206, which may be configured to receive one ormore selection inputs from a user or an input device manipulated by auser, wherein the selection inputs may correspond to a user selecting avirtual body part or a portion thereof. Furthermore, based on aselection input, selection input manager 206 may map a select locationassociated with a selection input to a virtual body part or a portionthereof, which may correspond to a virtual body part selected forsubsequent or concurrent action by the user.

Furthermore, virtual body part manager 204 may include a movement andaction input manager 208, which may be configured to receive one or moremovement and action inputs from a user and generate one or more displaycontrol signals that cause displayed movement and action of the virtualbody part. In an aspect, this displayed action may correspond to thevirtual body part or portion thereof selected by the user and mapped byselection input manager 106. Additionally, movement and action inputcomponent 208 may generate and display the displayed action based on theuser “dragging” “pointing” “tapping” “touching” or otherwise correctlymanipulating at least a portion of the virtual body part that is movablein virtual 3D space.

Furthermore, action input component 208 may base its virtual body partmovement and action generation and/or other processing actions on aparticular PEG, which may have been pre-selected by a user and loadedfor execution by processing engine 116. In an aspect, a movement andaction input may be input by a user and received by computer device 102as a result of the user partaking in such a PEG, other pre-actiontraining activity, or any other pre-action training activity.

Additionally, in an aspect of the present disclosure, a user inputmovement and action may be physically non-corresponding to the desiredor eventual action of the displayed virtual body part with which theuser is interacting. For purposes of the present disclosure, anon-corresponding movement and action may be a user action that differsrelatively significantly from a displayed movement and action by thevirtual body part.

For non-limiting example, suppose a user engaged in a pre-actiontraining activity wishes to move a virtual forearm directly upward usinga mouse as an input device. To do so, according to aspects of thedisclosure, the user may first navigate a cursor and click a mousebutton to select the virtual forearm on a display device, therebyinputting a selection input. Next, the user may keep the cursor on thevirtual forearm and may hold the mouse button down to signal a beginningof an action input. Thereafter, the user may drag the mouse two inchesalong a mouse pad, with the mouse button held down, and may observe thevirtual forearm rise upward, for example, from a virtual hip area to avirtual head area. To carry out this action, the user's forearm may havemoved approximately two inches in a direction parallel to the mouse pad,but resulted in a virtual action of the virtual forearm that was upwardin direction and appeared greater than two inches in magnitude.Therefore, this example user input action is non-corresponding to theaction of the virtual body part.

Additionally, virtual body part manager 204 may include a demonstrativeaction manager 210, which may be configured to provide display controlmessages to a display device to effectuate a demonstrative action of thevirtual body part. For example, demonstrative action manager 210 maystore and/or execute a retrieved demonstrative action to be displayed tothe user as a “ghost” action. In an aspect, the user may view thedemonstrative action and may then attempt to manipulate the virtual bodypart to mimic the action of the demonstrative action or ghost action.

Furthermore, virtual body part manager 204 may include a user-configuredUCI manager 212, which may tailor or otherwise configure a displayedvirtual body part to a user's body and/or alter the behavior of thedisplayed virtual body part based on one or more user characteristicvalues 222. In an aspect, such characteristics may include anatomicaland physiological data characteristic values associated with the user,such as without limitation height, weight, arm length, muscle mass,TBI-affected body parts, handedness, age, gender, eye/hair/skin color,and the like. In additional or alternative aspects, the usercharacteristics may include historical PEG performance data associatedwith the user, current neurological or chemical measurementcharacteristics or parameter values, or the like.

In an aspect, user-configured UCI manager 212 may obtain these usercharacteristic values 222 from memory 118. Alternatively,user-configured UCI manager 212 may obtain these user characteristicvalues from a source external to memory 118, such as, but not limitedto, a user measurement device configured to measure neurological and/orchemical characteristics of the user during pre-action trainingactivities, by querying a user or the user's trainer, doctor, coach,therapist or rehabilitation specialist for such characteristic valuesand receiving a characteristic value input in response, or otherwisereceiving user-specific performance, anatomical, physiological, or othercharacteristic values. In another aspect, UCI manager 212 obtains usercharacteristic values 222 by using anatomy recognition software known inthe art, such as WII™ or Kinect™, capable of detecting and identifyingbody parts and characteristics of human anatomical features.

In addition, user-configured UCI manager 212 may be configured tocompare the user characteristic values, or user parameters, to one ormore default parameters 224 stored in memory 118. In an aspect, defaultparameters 224 may comprise the parameters of a default virtual bodypart of the present disclosure and may include without limitationanatomical and physiological data (e.g., handedness, strength, bonelength, limitations on range of motion, skin characteristics, and thelike). Such characteristics may conform the behavior and attributes ofthe default virtual body part displayed to a user before tailoring,configuring, or otherwise customizing the virtual body part to the user.In order to perform such customization, the user-configured UCI manager212 may compare the obtained user characteristic values (e.g., usercharacteristic values 222) to default parameters 224. In an aspect,where the comparing determines that a user characteristic value differsfrom the default parameter value for a characteristic, theuser-configured UCI manager may set the compared parameter of thevirtual body part to be displayed to the user's characteristic value.Alternatively, where an obtained user characteristic value does notdiffer from the default parameter, user-configured UCI manager 212 mayleave the compared parameter unchanged.

an additional aspect, processing engine 116 may be configured togenerate and/or transmit one or more display control signals to thedisplay device to effectuate action of the virtual body part.Furthermore, processing engine 116 may be additionally configured tocalculate and/or report an action degree or action magnitude associatedwith an action of the virtual body part. In an aspect, processing engine116 may display the calculated action degree or action magnitude bygenerating one or more display control messages, which may be generatedand transmitted in substantially real time, for transmission to adisplay device for visual indication of the action degree to the user.

Furthermore, computer device 102 may include a memory 118, which may beconfigured to store information for utilization by other components in asystem, such as, but not limited to, processing engine 116. Suchinformation may include physical characteristic values 220, which mayinclude user characteristic values 222 associated with one or more usersand/or default parameters 224 associated with a baseline or default UCI,such as a virtual body part. Furthermore, memory 118 may storeneurological, chemical, or any other data related to a user's body(e.g., without limitation neurological signaling data or maps, neuronactivity data, etc.) generated and/or observed by a user measurementdevice before, during, and/or after a user engaging in pre-actiontraining. Such data may also be fed back to processing engine 116, whichmay alter a current or future PEG or pre-action training activity basedon the feedback.

In an additional aspect, such user data may be used to diagnose one ormore medical conditions. For example, computer device may output theuser data to a physician or other professional, who may analyze the dataand diagnose the medical condition. In an alternative or additional andnon-limiting example, computer device 102 may contain instructionsexecutable by processing engine 116 to automatically diagnose a medicalcondition based on the user data stored on memory 118.

In addition, memory 118 may include executable instructions (e.g.,executed by processing engine 116), that when performed, allow the userto engage in one or more pre-action training activities. As used herein,pre-action training activities may include interactive electronic gamesor activities, such as, but not limited to, Pre-Action Exercise Games(PEGs) 226. The PEGs 226 may govern the behavior of a virtual body partin response to one or more inputs by a user during pre-action trainingactivities.

Additionally, cognitive and nervous system functions are involved in allPEGs. According to some example PEGs, virtual upper body parts arepresented to a user to control in order to simulate purposeful physicalmovements and actions—for example, opening and closing a virtual hand.Some PEGs may be virtual task games, which may couple player control ofvirtual body parts and objects to accomplish tasks and/or solveproblems—for example, dropping a spoon into a cup.

Furthermore, in an aspect, PEGs may include player control of any partor all of an affected hand, lower or upper arm (right or left),executing flexion/extension, supination/pronation, abduction/adduction,or any other extremity or body part action in any direction. Accordingto the PEGs contemplated herein, users can manage displays of some of,the majority of, or all of a virtual upper extremity from substantiallyany angle. Additionally, the virtual body part may comprise fingers,which may be manipulated individually or in combination. The virtualbody part may comprise a wrist, which may be flexed/extended,abducted/adducted, or supinated/pronated. Furthermore, according to somenon-limiting example PEGs, the virtual body part may comprise an arm,wherein the lower and upper arm may be manipulated independently or incombined action of any and all joints of the arm, wrist and hand.

In some non-limiting example PEGs, where the virtual body part is avirtual hand, example games for pre-action training may include:

pincer action to grasp a key;

two finger actions to grasp a ball and drop it into a cup;

multi-finger action to pick up a spoon and drop it into a cup;

full hand grasp around a mug handle;

tapping actions by index and middle fingers on a remote controller;

hand grasps of objects shaped as stars, circles or squares, thenplacement in similarly shaped slots.

Regarding virtual body parts in some non-limiting example PEGs where thevirtual body part includes a virtual arm and/or a virtual hand, examplegames for pre-action training may include:

opening a correct box, i.e. selecting and opening the correct numberedand colored box (e.g., purple 24) in a circle of nine boxes, afterobservations and computations as elementary as choosing the (single)“lowest purple box bearing an even number” (purple 24 is correct) tocomputations based on several numbered boxes, e.g., “choose the highestblue even numbered box, subtract the second of its numbers from thefirst, square it and find the green box with that result” (if 92 blue isselected the subtraction yields number 7, which when squared is 49, sogreen box 49 is correct);

same as above, nine box game with voice instructions to the player;

similar open the box game in a more elementary vertical presentation offive boxes;

light bulb game requiring the player to unscrew a light bulb, choose thecorrect lettered socket and screw the bulb into the correct socket;

playing card games, for example in a simple game the virtual arm andhand are controlled to select a pair of twos, place that pair, rightside up on a surface, then the player must choose the lowest numberedpair that wins over a pair of twos, alternately the highest numberedpair that wins over twos, then the lowest (or highest) pair of picturecards that wins over twos and so forth, to more complex combinations ofplaying cards/hands;

puzzle games in which the cursor may be used to move 6, 9 or 16 puzzlepieces to assemble a complete representation of any display noted above.For example, a hand image, in any orientation, position andconfiguration may be disassembled by the puzzle game into 6, 9 or 16puzzle pieces to be reassembled by the player, or a more complexdisassembly of the nine box arm game may be “puzzled”;

simple number game displaying 0-9 and processes (add, subtract,multiply, divide and equals sign) and calling for the PEGs player to usea virtual arm and hand to select numbers and processes and to make anynumber of computations by arraying the numbers and processes accurately;

simple letter game displaying all letters of the alphabet and callingfor the PEGs player to use a virtual arm and hand to select letters tomake any number of words by arraying the letters accurately.

Where the virtual body part is at least one virtual muscle, games forpre-movement and action training may include selection of the at leastone virtual muscle to cause it to contract or relax at any rate of speedor to stop, for non-limiting example to end cramping or focal cervicaldystonia or to regain movement impeded by hand dystonia. Therefore byloading and/or executing the one or more stored PEGs 226 of memory 118,computer device 102 may present a user with a UCI, such as a virtualbody part, with which the user may interact to participate in pre-actiontraining activities.

In a further aspect, computer device 102 may include a body part deviceinterface component 228, which may be configured to interface with anexternal (or integrated) body part device 128, generate one or morecontrol signals based on the user control of the virtual body part, orUCI, and transmit the one or more control signals to the body partdevice 128 of FIG. 1 for eventual stimulation of a target body part 150.In some examples, body part device interface component 228 may include abody part device computing manager 230 which may generate the one ormore control signals based on the user control of the virtual body part.In a further aspect, the body part device computing manager 230 mayinclude a transmitter 232, which may be communicatively coupled to thebody part device 128 via a communicative connection and may beconfigured to transmit the one or more control signals to the body partdevice 128. In some examples, the transmitter 232 may transmit thesignals wirelessly or via a transmission line, depending on whether thecomputer device 102 is tethered to the body part device 128 via atransmission line, such as a bus or other wire. For example, where thecomputer device 102 is connected to the body part device 128, thetransmitter may be configured to transmit the control signals over thetransmission line (though it may also transmit the control signalswirelessly as well). Alternatively, where the computer device 102 is nottethered to the body part device, the transmitter 232 may transmit theone or more control signals wirelessly. As such, transmitter 232 maycomprise one or more antennas or transceivers.

Turning to FIG. 3, the figure illustrates an example UCI creating device300 that facilitates creation of UCIs, including one or more virtualbody parts. In an aspect, UCI creating device 300 may include ananatomical and physiological data obtaining component 302, which may beconfigured to obtain anatomical and physiological data associated withone or more animal species, including, but not limited to, human beings.Such anatomical and physiological data may be accurate or relativelyaccurate anatomical and physiological data to ensure that a relativelylife-like UCI may be created therefrom. In a non-limiting example,anatomical and physiological data obtaining component 302 may beconfigured to interface, communicate with, read, extract data from, orobtain data from an external device or component that contains suchanatomical and physiological data, such as, but not limited to a server,a device connected to a network (e.g the Internet), a wireless device,or a device connected to UCI creating device by hard wire communicationline. In an additional aspect, anatomical and physiological dataobtaining component 302 may be configured to prompt a user to manuallyinput anatomical and physiological data and receive such data from auser via an input device such as, but not limited to, a keyboard.

Additionally, UCI creating device 300 may include a memory 304, whichmay include one or more databases 306 for storing and organizing data.In an aspect, database 306 may store anatomical and physiological data308, which may have been obtained via anatomical and physiological dataobtaining component 302.

Furthermore, UCI creating device 300 may include a UCI creatingcomponent 310, which may be configured to receive one or more inputs,such as, but not limited to program instructions, from a user (e.g., UCIarchitect, programmer, graphic designer), wherein the inputs, whenexecuted, construct a UCI. In an aspect, the received inputs mayconstruct the UCI based on the stored anatomical and physiological data308. Furthermore, UCI creating component may include an executableprogram, such as an image design program, graphics creation suite,programming/compiling engine, or rendering suite, which UCI creatingcomponent 310 may execute to receive the one or more inputs from theuser. These one or more inputs may define the physical parameters of theUCI, such as, but not limited to the bone length, bone interaction andposition, tendon length and position, skin tone, and the like.Furthermore, the inputs may form computer-executable instructions thatdefine and/or otherwise control the behavior of the UCI or portions ofthe UCI when executed, displayed, and interacted with by a user, forexample, during pre-action training such as when playing a PEG. Inaddition, inputs may define the behavior of virtual body parts adjacentto the selected or moved body parts such that action of one virtual bodypart or portion thereof causes related action of the adjacent virtualbody part or a portion thereof.

Moreover, UCI creating device 300 may include a PEG creating component312, which may be configured to create one or more PEGs by receiving oneor more inputs, such as, but not limited to program instructions, from auser (e.g., PEG architect, programmer), wherein the inputs, whenexecuted, construct a PEG. The created PEG may be created for purposesof pre-action training and may be programmed to alter the behavior of aUCI, such as a virtual body part, based upon user inputs. Furthermore,the PEG may be programmed to customize or tailor a PEG based on uniquecharacteristic data associated with the user, such as, but not limitedto, height, weight, historical PEG performance, handedness, extremitylength, and the like.

Referring to FIG. 4, in one aspect, generic computer device 400 mayinclude a specially programmed or configured computer device, and mayrepresent or contain components that may be included in computer device102 FIGS. 1 and 2) or UCI creating device 300 (FIG. 3) or body partdevice 128. Generic computer device 400 includes a processor 402 forcarrying out processing processes associated with one or more ofcomponents and processes described herein. Processor 402 can include asingle or multiple set of processors or multi-core processors. Moreover,processor 402 can be implemented as an integrated processing systemand/or a distributed processing system. Additionally, processor 402 maybe configured to perform the processes described herein related to UCIbehavior and/or pre-action training on the generic computer device 400.

Generic computer device 400 further includes a memory 404, such as forstoring data used herein and/or local versions of applications beingexecuted by processor 402. Memory 404 can include any type of memoryusable by a computer, such as random access memory (RAM), read onlymemory (ROM), tapes, magnetic discs, optical discs, volatile memory,non-volatile memory, and any combination thereof. Additionally, memory404 may be configured to store data and/or code or computer-readableinstructions for performing the processes described herein related tocreating, controlling, manipulating, and/or instantiating a UCI.

Further, generic computer device 400 includes a communications component406 that provides for establishing and maintaining communications withone or more entities utilizing one or more of hardware, software, andservices as described herein. Communications component 406 may carrycommunication signals between components on generic computer device 400,as well as exchanging communication signals between generic computerdevice 400 and external devices, such as devices located across a wiredor wireless communications network and/or devices serially or locallyconnected to generic computer device 400. For example, communicationscomponent 406 may include one or more buses, and may further includetransmit chain components and receive chain components associated with atransmitter and receiver, respectively, or a transceiver, operable forinterfacing with external devices.

Additionally, generic computer device 400 may further include a datastore 408, which can be any suitable combination of hardware and/orsoftware, that provides for mass storage of information, databases, andprograms employed in connection with aspects described herein. Forexample, data store 408 may be a data repository for applications anddata not currently being executed by processor 402, such as thoserelated to the aspect described herein. In addition, generic computerdevice 400 may contain an input/output component 410, which may beconfigured to interface with one or more external devices, such as aninput device (e.g., input device, user measurement device (FIG. 1))and/or an output device (e.g., a display, feedback device, or externalbody part device (FIG. 1)). Specifically, input/output component 410 maycontain circuitry and/or instructions that allow generic computer device400 to connect to and/or communicate with these external devices.

In reference to FIG. 5, illustrated is an example methodology 500 forcreating or otherwise constructing a user-controllable image, such as avirtual body part. In an aspect, at block 502, a user (e.g., a programengineer, user, or graphics engineer) or computer device may obtainanatomical and physiological data associated with a body. Once obtained,at block 504, the user or computer device may store the anatomical andphysiological data in a database. In addition, at block 506, the user orcomputer device may create the user-controllable image based on thestored anatomical and physiological data. Furthermore, the createduser-controllable image may be configurable to a user. Additionally,according to some example methods, at least a moveable portion of theuser-controllable image may be constructed to move based on input from auser, for example, so as to enable pre-action training the user.

Furthermore, FIG. 6 presents an example methodology 600 for configuring,tailoring, or otherwise customizing a UCI or related PEG to a particularuser. Such a method may be performed by a computer device, but may alsobe performed or controlled via a computer device by an individual, e.g.,a pre-action training coach, therapist, or doctor, who may guide a userthrough a pre-action training regimen. In an aspect, at block 602, theindividual or computer device may obtain at least one default parameterassociated with the user-controllable image. In addition, at block 604,the individual or computer device may obtain at least one user parameterassociated with a user body. Furthermore, at block 606, the individualor computer device may compare the at least one default parameter andthe at least one user parameter. Moreover, the individual or computerdevice may construct a user-configured user-controllable image byadjusting one or more of the at least one default parameter. In anaspect, such an adjustment may be made where the at least one userparameter differs from the at least one default parameter. Additionally,the user-configured user-controllable image may be configured so as toenable pre-training a user, and as such, at block 610, the individual orcomputer device may provide the user-configured user-controllable imageto the user for pre-action training.

Turning to FIG. 7, an example methodology 700 is presented forpresenting a controllable virtual body part to a user. In an aspect, atblock 702, a computer device may provide a virtual body part to a user.Furthermore, at block 704, the computer device may receive a selectioninput from the user, wherein the selection input may be associated withat least a portion of the virtual body part. Additionally, at block 706,the computer device may receive an action input from the user.Furthermore, at block 708, the computer device may cause the display ofan action of the at least a portion of the virtual body part based onthe action input. In an additional aspect, the action may be physicallynon-corresponding to the action input. Furthermore, the selection inputand action input may be at least a part of pre-training a user.

Turning to FIG. 8, an example methodology 800 is presented forpresenting a controllable virtual body part to a user. In an aspect, atblock 802, a computer device may provide a virtual body part to a uservia a display device. Furthermore, at block 804, the computer device mayreceive a selection input and an action input from the user. In someaspects, the selection input and the action input may be associated withat least a portion of the virtual image, which may include a virtualbody part. Furthermore, the selection input and action input may be atleast a part of pre-training a user. Additionally, at block 806,methodology 800 may include instantiating virtual movement of thevirtual image. In an aspect, block 806 may be, in a non-limiting aspect,performed by a computer device or by the user. Furthermore, at block808, the methodology 800 may include reinitiating neurologicalfunctionality based on the instantiating. In an aspect, block 808 maybe, in a non-limiting aspect, performed by a computer device or by theuser.

Referring to FIG. 9, an example system 900 is displayed for creating aUCI. For example, system 900 can reside at least partially within one ormore computing or processing devices. It is to be appreciated thatsystem 900 is represented as including functional blocks, which can befunctional blocks that represent processes implemented by a processor,software, or combination thereof (e.g., firmware). System 900 includes alogical grouping 902 of electrical components that can act inconjunction. For instance, logical grouping 902 can include anelectrical component 904 for obtaining anatomical and physiological dataassociated with a body. In an aspect, electrical component 904 maycomprise anatomical and physiological data obtaining component 302 (FIG.3). In addition, logical grouping 902 can include an electricalcomponent 906 for storing the anatomical and physiological data in adatabase. In an aspect, electrical component 906 may comprise UCIcreating device 300, memory 304 (FIG. 3), or processor 402 (FIG. 4). Inaddition, logical grouping 902 can include an electrical component 908for creating a UCI based on the stored anatomical and physiologicaldata. In an aspect, electrical component 908 may comprise UCI creatingcomponent 310 (FIG. 3).

Additionally, system 900 can include a memory 910 that retainsinstructions for executing processes associated with the electricalcomponents 904, 906, and 908, stores data used or obtained by theelectrical components 904, 906, and 908, etc. While shown as beingexternal to memory 910, it is to be understood that one or more of theelectrical components 904, 906, and 908 can exist within memory 910. Inone example, electrical components 904, 906, and 908 can comprise atleast one processor, or each electrical component 904, 906, and 908 canbe a corresponding module of at least one processor. Moreover, in anadditional or alternative example, electrical components 904, 906, and908 can be a computer program product including a computer readablemedium, where each electrical component 904, 906, and 908 can becorresponding code.

Referring to FIG. 10, an example system 1000 is displayed for creating aUCI. For example, system 1000 can reside at least partially within oneor more computing or processing devices. It is to be appreciated thatsystem 1000 is represented as including functional blocks, which can befunctional blocks that represent processes implemented by a processor,software, or combination thereof (e.g., firmware). System 1000 includesa logical grouping 1002 of electrical components that can act inconjunction. For instance, logical grouping 1002 can include anelectrical component 1004 for obtaining at least one default parameterassociated with a UCI. In an aspect, electrical component 1004 maycomprise computer device 102 (FIGS. 1 and 2). In addition, logicalgrouping 1002 can include an electrical component 1006 for obtaining atleast one user parameter associated with a user body. In an aspect,electrical component 1006 may comprise computer device 102 (FIGS. 1 and2). In addition, logical grouping 1002 can include electrical component1008 for comparing the at least one default parameter and the at leastone user parameter. In an aspect, electrical component 808 may compriseuser-configured UCI manager 212 (FIG. 2). In addition, logical grouping1002 can include an electrical component 1010 for constructing auser-configured UCI by adjusting one or more of the at least one defaultparameter. In an aspect, electrical component 1010 may compriseuser-configured UCI manager 212 (FIG. 2). In addition, logical grouping1002 can include an electrical component 1012 for providing theuser-configured UCI to the user for pre-action training. In an aspect,electrical component 1012 may comprise computer device 102 (FIGS. 1 and2).

Additionally, system 1000 can include a memory 1010 that retainsinstructions for executing processes associated with the electricalcomponents 1004, 1006, 1008, 1010, and 1012, stores data used orobtained by the electrical components 1004, 1006, 1008, 1010, and 1012,etc. While shown as being external to memory 1010, it is to beunderstood that one or more of the electrical components 1004, 1006,1008, 1010, and 1012 can exist within memory 1010. In one example,electrical components 1004, 1006, 1008, 1010, and 1012 can comprise atleast one processor, or each electrical component 1004, 1006, 1008,1010, and 1012 can be a corresponding module of at least one processor.Moreover, in an additional or alternative example, electrical components1004, 1006, 1008, 1010, and 1012 can be a computer program productincluding a computer readable medium, where each electrical component1004, 1006, 1008, 1010, and 1012 can be corresponding code.

Referring to FIG. 11, an example system 1100 is displayed for creating aUCI. For example, system 1100 can reside at least partially within oneor more computing or processing devices. It is to be appreciated thatsystem 1100 is represented as including functional blocks, which can befunctional blocks that represent processes implemented by a processor,software, or combination thereof (e.g., firmware). System 1100 includesa logical grouping 1102 of electrical components that can act inconjunction. For instance, logical grouping 1102 can include anelectrical component 1104 for providing a virtual body part to a user.In an aspect, electrical component 1104 may comprise computer device 102(FIGS. 1 and 2). In addition, logical grouping 1102 can include anelectrical component 1106 for receiving a selection input from the userassociated with at least a portion of the virtual body part. In anaspect, electrical component 1106 may selection input manager 206 (FIG.2). In addition, logical grouping 1102 can include an electricalcomponent 1108 for receiving an action input from the user. In anaspect, electrical component 1108 may comprise action input manager 208(FIG. 2). In addition, logical grouping 1102 can include an electricalcomponent 1110 for displaying a action of the portion of the virtualbody part based on the action input. In an aspect, electrical component1110 may comprise computer device 102 (FIGS. 1 and 2).

Additionally, system 1100 can include a memory 1110 that retainsinstructions for executing processes associated with the electricalcomponents 1104, 1106, 1108, and 1110, stores data used or obtained bythe electrical components 1104, 1106, 1108, and 1110, etc. While shownas being external to memory 1110, it is to be understood that one ormore of the electrical components 1104, 1106, 1108, and 1110 can existwithin memory 1110. In one example, electrical components 1104, 1106,1108, and 1110 can comprise at least one processor, or each electricalcomponent 1104, 1106, 1108, and 1110 can be a corresponding module of atleast one processor. Moreover, in an additional or alternative example,electrical components 1104, 1106, 1108, and 1110 can be a computerprogram product including a computer readable medium, where eachelectrical component 1104, 1106, 1108, and 1110 can be correspondingcode.

Referring to FIG. 12, an example system 1200 is displayed forinstantiating virtual movement of a virtual image and reinitiatingneurological functionality. For example, system 1200 can reside at leastpartially within one or more computing or processing devices. It is tobe appreciated that system 1200 is represented as including functionalblocks, which can be functional blocks that represent processesimplemented by a processor, software, or combination thereof (e.g.,firmware). System 1200 includes a logical grouping 1202 of electricalcomponents that can act in conjunction. For instance, logical grouping1202 can include an electrical component 1204 for providing a virtualimage to a user via a display device. In addition, logical grouping 1202can include an electrical component 1206 for receiving a selection inputand an action input from the user. In addition, logical grouping 1202can include an electrical component 1208 for instantiating virtualmovement of the virtual image. In addition, logical grouping 1202 caninclude an electrical component 1210 for reinitiating neurologicalfunctionality based on the instantiating. In an aspect, system 1200 maycomprise computer device 102 (FIGS. 1 and 2).

Additionally, system 1200 can include a memory 1212 that retainsinstructions for executing processes associated with the electricalcomponents 1204, 1206, 1208, and 1210, stores data used or obtained bythe electrical components 1204, 1206, 1208, and 1210, etc. While shownas being external to memory 1212, it is to be understood that one ormore of the electrical components 1204, 1206, 1208, and 1210 can existwithin memory 1212. In one example, electrical components 1204, 1206,1208, and 1210 can comprise at least one processor, or each electricalcomponent 1204, 1206, 1208, and 1210 can be a corresponding module of atleast one processor. Moreover, in an additional or alternative example,electrical components 1204, 1206, 1208, and 1210 can be a computerprogram product including a computer readable medium, where eachelectrical component 1204, 1206, 1208, and 1210 can be correspondingcode.

FIG. 13 is a representative drawing of a system 1300, which may includea non-virtual robot 1301, which may be configured to move in response toan input from a user. In an aspect, such input may be anon-corresponding movement input by an input device, such as a mouse, ina manner according to one or more methods provided herein. In an aspect,non-virtual robot 1301 may comprise a prosthesis, powered orthoticdevice, exoskeleton, or other motorized device that may physically movein response to one or more inputs or pre-programmed or pre-recodedcontrols

Additionally, non-virtual robot 1301 may include a motor 1302, which maybe a uni- or bi-directional motor for moving one or more moveablesubstructures 1308, which may comprise one or more parts of non-virtualrobot 1301, such as, but not limited to a finger, limb, head, foot,hand, etc. Some actuator technologies or body part designs may utilize aplurality of motors 1302 (or other actuators) to move the one or moremoveable substructures 1308. Further, to create such movement,non-virtual robot 1301 may include a clutch 1304 and/or a gearbox 1306for controlling aspects of the movement of moveable substructure 1308,such as, but not limited to, speed, force, etc.

Furthermore, system 1300 may include a controller 1312, which may beconfigured to control motor 1302 and/or any other component ofnon-virtual robot 1301 based on one or more inputs. In an aspect, theseone or more inputs may comprise non-corresponding input from a userand/or a feedback input output by one or more sensors 1310, which may beconfigured to sense and/or analyze movement of the one or more moveablesubstructure 1308.

FIG. 14 is a representative wiring diagram of a device 1400, which maycomprise a non-virtual robot, powered orthotic device, prosthesis, orexoskeleton body part, such as, but not limited to, non-virtual robot1301 of FIG. 13. In an aspect, device 1400 may utilize a manual switch1406 to engage either of the bi-directional circuits 1404 forcontrolling a motor 1402, which may be a bi-directional motor. In anaspect, manual switch 1406 may be a three-position Double Pole DoubleThrow (2P2T) switch for engaging either open or close operation, andwhich may be center-loaded for neither engagement. Furthermore, device1400 may include a pair (or more than two) of limit switches 1404corresponding to two (or more) interleaved circuits (extensor andflexor, i.e. open and close), which may limit motion associated withmotor 1402.

FIG. 15 is a representative wiring diagram of a device 1500, which maybe a non-virtual robot, powered orthotic device, prosthesis, orexoskeleton body part (e.g., of FIGS. 13 and/or 14). In an aspect,device 1500 may operate in response to one or more digital outputs 1508from a computing device 1510, which may control the movement of device1500 and the associated motor 1502. For example, the digital outputs1508 may engage bi-directional circuits, which may incorporate the 2P2Tswitch circuits present in FIG. 14 (not shown here). Furthermore,current amplifiers 1506 (or voltage amplifiers) may amplify the one ormore digital outputs 1508 (or analog outputs) to cause movement viamotor 1502. Also, though not shown in FIG. 15, device 1500 may include aplurality of sensors capable of being incorporated which each of one ormore body part structures or sub-structures (e.g., moveable substructure1308 of FIG. 13).

FIG. 16 is a block diagram illustrating a machine in the example form ofa computer system 1600, within which a set or sequence of instructionsfor causing the machine to perform any one of the methodologiesdiscussed herein may be executed, according to an example embodiment. Inalternative embodiments, the machine operates as a standalone device ormay be connected (e.g., networked) to other machines. In a networkeddeployment, the machine may operate in the capacity of either a serveror a client machine in server-client network environments, or it may actas a peer machine in peer-to-peer (or distributed) network environments.The machine may be a personal computer (PC), a tablet PC, a set-top box(STB), a Personal Digital Assistant (PDA), a mobile telephone, a webappliance, a network router, switch or bridge, a cloud-based computingdevice, or any machine capable of executing instructions (sequential orotherwise) that specify actions to be taken by that machine. Further,while only a single machine is illustrated, the term “machine” shallalso be taken to include any collection of machines that individually orjointly execute a set (or multiple sets) of instructions to perform anyone or more of the methodologies discussed herein.

Example computer system 1600 includes at least one processor 1602 (e.g.,a central processing unit (CPU), a graphics processing unit (GPU) orboth, processor cores, compute nodes, etc.), a main memory 1604 and astatic memory 1605, which communicate with each other via a link 1608(e.g., bus). The computer system 1600 may further include a videodisplay unit 1610, an alphanumeric input device 1612 (e.g., a keyboard),and a user interface (UI) navigation device 1614 (e.g., a mouse). In oneembodiment, the video display unit 1610, input device 1612 and UInavigation device 1614 are incorporated into a touch screen display. Thecomputer system 1600 may additionally include a storage device 1615(e.g., a drive unit), a signal generation device 1618 (e.g., a speaker),a network interface device 1620, and one or more sensors (not shown),such as a global positioning system (GPS) sensor, compass,accelerometer, or other sensor.

The storage device 1615 includes a machine-readable medium 1622 on whichis stored one or more sets of data structures and instructions 1624(e.g., software) embodying or utilized by any one or more of themethodologies or functions described herein. The instructions 1624 mayalso reside, completely or at least partially, within the main memory1604, static memory 1605, and/or within the processor 1602 duringexecution thereof by the computer system 1600, with the main memory1604, static memory 1605, and the processor 1602 also constitutingmachine-readable media.

While the machine-readable medium 1622 is illustrated in an exampleembodiment to be a single medium, the term “machine-readable medium” mayinclude a single medium or multiple media (e.g., a centralized ordistributed database, and/or associated caches and servers) that storethe one or more instructions 1624. The term “machine-readable medium”shall also be taken to include any tangible medium that is capable ofstoring, encoding or carrying instructions for execution by the machineand that cause the machine to perform any one or more of themethodologies of the present disclosure or that is capable of storing,encoding or carrying data structures utilized by or associated with suchinstructions. The term “machine-readable medium” shall accordingly betaken to include, but not be limited to, solid-state memories, andoptical and magnetic media. Specific examples of machine-readable mediainclude non-volatile memory, including, by way of example, semiconductormemory devices (e.g., Electrically Programmable Read-Only Memory(EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM))and flash memory devices; magnetic disks such as internal hard disks andremovable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

The instructions 1624 may further be transmitted or received over acommunications network 1626 using a transmission medium via the networkinterface device 1620 utilizing any one of a number of well-knowntransfer protocols (e.g., HTTP, XML). Examples of communication networksinclude a local area network (LAN), a wide area network (WAN), theInternet, mobile telephone networks, Plain Old Telephone (POTS)networks, and wireless data networks (e.g., Wi-Fi, 3G, and 4G LTE/LTE-Aor WiMAX networks). The term “transmission medium” shall be taken toinclude any intangible medium that is capable of storing, encoding, orcarrying instructions for execution by the machine, and includes digitalor analog communications signals or other intangible medium tofacilitate communication of such software.

Referring to FIGS. 17A and 17B in combination with FIGS. 1-2, one aspectof virtual body part 1700 is shown to illustrate an example of system100 in use with pre-movement and pre-action self-re-training/re-learningwhere the user seeks to self-re-learn or self-learn to perform aphysical movement and action. System 100 includes computer device 102,input device 104, and display device 106. In this example, virtual bodypart 1700 is a left forearm 1702 including hand 1704 and index finger1706. Selection input manager 206 of system 100 has mapped selectlocations associated with selection input to virtual body part 1700 andparts thereof corresponding to simulated movement and actions by virtualbody part 1700. These select locations correspond to a user's body partthat requires physical motor and related cognitive and nervous systemimprovements. Movement and action input manager 208 is configured toreceive movement and action inputs from user 120 and system 100generates one or more display control signals that cause virtual bodypart 1700 to perform a movement and action.

For example, in response to user input, the user views a demonstrativemovement and action of index finger 1706 moving from a firstconfiguration in which index finger 1706 is extended as shown in FIG.17A to a second configuration in which index finger 1706 is flexed asshown in FIG. 17B. Index finger moves from the extended configuration tothe flexed configuration by virtually stimulating a flexor muscle 1708corresponding to index finger 1706. Index finger 1706 moves back to theextended configuration by releasing (or ceasing to stimulate) flexormuscle 1708 and stimulating an extensor muscle 1710 corresponding toindex finger 1706. Optionally, system 100 communicates a signal to one,some, or all of a feedback device 130, body part device 128, or targetbody part 150 of user 120.

In one embodiment, for example, input device 104 is a computer mousewhere the user's selection is input to system 100 using the computermouse to move a cursor 1712 to a location and then clicking the mousebutton to make a selection. For example, user 120 uses the computermouse to move cursor 1712 to and click on forearm 1702. User 120 canclick on forearm 1702 generally, click on a part of forearm 1702 (e.g.,anterior portion), click on a particular region of forearm 1702 (e.g., aparticular muscle), by moving to and clicking on a list, menu 1714 orindicia 1716 (e.g., shaded region). Selections available to the user canbe configured based on a level of detail chosen for the task to becompleted, where the level of detail can be adjusted based on the user'sabilities. For example, PEG level is set so that user 120 must selectthe particular muscle that moves index finger 1706. Similarly, PEG levelcan be set so that user 120 must only generally select forearm 1702 ornear forearm 1702 to have the system display the same movement andaction of index finger 1706.

In one embodiment, system 100 indicates the muscle or muscle group usedand/or a sequence of muscle movement and actions required to perform amovement and action selected by user 120 or perform a movement andaction. For example, non-stimulated muscles of virtual body part 1700(i.e., muscles at rest) are displayed in one color or intensity (e.g.,brown/tan or low intensity) and muscles actively being stimulated aredisplayed in a second color or intensity (e.g., red or high intensity).Thus, in the virtual body part 1700 shown in FIG. 17B, a virtual hand1704, forearm 1702, and extensor muscle 1710 are displayed in browncolor on display device 106. As flexor muscle 1708 is stimulated, system100 displays flexor muscle 1708 of the virtual forearm 1702 in red coloror using other indicia 1716 in addition to displaying movement of indexfinger 1706 from the first configuration (i.e., finger extended) to thesecond configuration (i.e., finger flexed) and remaining in thatconfiguration as long as the flexor muscle 1708 is stimulated. As shownin FIG. 17B, a stimulated flexor muscle 1708 is accentuated on displaydevice 106 by using indicia 1716 while index finger 1706 is maintainedin the flexed configuration.

Referring to FIG. 18, a perspective view shows another aspect of virtualbody part 1800 performing a task of grasping and moving a virtual coffeemug 1810. Virtual body part 1800 includes upper arm 1802, forearm 1804,and hand 1806. User 120 selects and moves virtual body part 1800 asindicated by cursor 1812. In this example, user 120 may raise or lowerforearm 1804 by clicking on bicep muscle 1814, which is emphasized ondisplay device 106 by indicia 1816 shown in FIG. 18 as cross-hatching.Using a computer mouse (not shown) as input device 104, for example,user 120 alternately may raise or lower forearm 1804 by clicking cursor1812 on forearm 1804 and dragging the computer mouse linearly to causeforearm 1804 to pivot upwards or downwards about elbow 1818. Thus, themovement and action of user 120 is non-corresponding to the displayedmovement and action of virtual body part 1800 since the actual linearmovement of a computer mouse on a table or other surface does notcorrespond to the simulated pivoting movement and action of forearm 1804and also does not correspond to the same amount of simulated movement asdisplayed. In this example, user 120 selects hand 1806 to open or closea grasp on coffee mug 1810. User 120 also may orient and align virtualbody part 1800 in 3D virtual space by changing the displayed view ofvirtual body part 1800 and using input device 104 to cause movementsneeded to relocate, pick up/set down, grasp/release, rotate, orotherwise move coffee mug 1810.

Referring now to FIG. 19, an example of a pre-movement and pre-actionexercise game (PEG) is illustrated as displayed to the user usingdisplay device 106 (not shown). The user is instructed to use virtualbody part 1900 to select and move parts of a virtual block game 1910.The user controls virtual body part 1900 to select blocks 1912, 1916 andplace them into corresponding recesses 1914, 1918, respectively. Virtualgame 1900 is an example of the user being instructed to apply a rule(e.g., matching the block shape 1912 with a shape of recess 1914) and acondition to be met (e.g., placing block 1912 into recess 1914).

One or more default virtual body parts may be pre-programmed and storedin a memory structure such as memory 118, as discussed above, for usewith the aforementioned methods and system. Each pre-programmedinteractive and controllable virtual body part is a digital anatomicalvirtual extremity (DAVE). DAVEs may be stored on any digital device and,combined with the user's input controls of the DAVEs presented anddisplayed, for interactive user controlled/directed purposeful simulatedphysical movements. Rehabilitation and/or therapy for users with ABI asdescribed herein may include use of DAVEs. DAVEs may be utilized withany digital device for providing user therapy. DAVE's may be one form ofthe UCIs utilized to play pre-action exercise games (PEGs) as describedhereinabove.

The methods and system described herein provide a new therapy byproviding: (a) survivor (synonymously user) controllable digitalanatomical virtual extremities (DAVEs) on any digital device/screen; (b)combining the survivors' input controls of DAVEs presented/displayed andinteractively survivor-controlled/directed to make purposeful simulatedphysical movements; with (c) concurrent communication from controlledDAVEs to body part devices, exoskeletons, gloves and other complexmulti-point interfaces thereby enabling self-administered physicalmovement therapies to one or more impaired or affected body parts. Inthis manner, survivors not only exercise brain processes in controllingand directing DAVEs but, in addition self-administer physical movementtherapies to one or more body parts.

In one embodiment, DAVE's may be personally, independently andinteractively survivor-controlled and directed. By interacting withDAVE's, each survivor's brain processes are exercised through theprocess of selecting and making command inputs resulting in virtualmovements of body parts also known as purposeful, simulated physicalmovements of DAVEs. The simulated physical movements represent asurvivor's present tense (real-time), virtually interactive anatomicalmovement controls and directions. Selection of and interacting withDAVEs follows each survivor's initial kinetic imagery (visualization) ofeach desired movement. Therefore, kinetic imagery (visualization) isinstantiated by controlling/directing DAVEs to make intended,purposeful, simulated physical, movements that each survivor would makeabsent injury/impairment. Feedback from DAVE actions is close tofeedback from actual physical actions thereby fostering improved furtherinteractions.

Alternatively, or additionally, DAVEs may be pre-coded to include aplurality of movements such as a predetermined series of movement. Thisseries of virtual movements is activated or initiated by a particularmovement or selection made by the user. For example, in furthernon-limiting embodiments, pre-coded DAVEs may include interactions withother digital representations such as interactions with icons, avatarsand/or other images which represent virtual extremities, body partsand/or object images. Pre-coded DAVEs are user-activated so thatdisplayed simulated physical movements reflect the users' movementgoals, but the anatomical tactics for the way, i.e. the how to make themovements, may be decided (past tense), pre-coded and/or game designed.

In one aspect, users may be presented with opportunities to conjoinDAVEs and pre-coded DAVEs in order to simulate physical movements whenat least two extremities (body parts) and/or objects are involved.Non-limiting examples of conjoined DAVEs include simulating when oneextremity grasps and another extremity twists (opening a closedcontainer), operates a tool (hammers a nail, turns a screw), or keypunches (as in holding a mobile phone with one hand and tapping numbersof a phone number with another hand) or any other task where at leasttwo extremities and/or objects are involved. Thus, the conjoinedembodiments described herein makes it possible fortherapy/rehabilitation to include one or more DAVEs interacting withvirtual images, avatars, icons and the like. The conjoined embodimentprocess most closely tracks and mimics what the ABI survivor could dopre-brain injury or condition and most directly exercises the brain tore-train for re-gaining/restoring brain-motor control and command ofimpaired extremities.

The methods, system and systems described herein are directed toassisting survivors of acquired brain injury (ABI) traumatic braininjury, autism spectrum disorder, focal dystonia and otherbrain-affected individuals by providing, on any digital device which maypresent or display to users, a combination of DAVEs in any of manyforms. By non-limiting example, DAVEs may represent:

a single, interactively controllable virtual extremity representing theusers affected physical extremity;

multiple, interactively controllable virtual extremities representingthe users affected physical extremities;

a single interactively controllable virtual extremity representing theuser's unaffected physical extremity;

multiple, interactively controllable virtual extremities representingthe users unaffected physical extremities;

single or multiple virtual extremities representing both the user'saffected and unaffected physical extremities, being programmed to makesimulated physical movements according to a design and purpose.

DAVEs may be personally, realtime, interactively and tacticallycontrolled and/or directed by users to make custom-user-purposedsimulated physical movements.

In a further non-limiting embodiment, the methods and system describedherein may present or display conjoined forms of DAVEs to simulatephysical movements by the user's present tense actions, controls, and/ordirections, which instantiate each user's personal kinetic imagery. Thiskinetic imagery instantiation is triggered by controlling/directingvirtual DAVEs. The use of pre-coded DAVEs is to cause a simulatedmovement goal to be reached. The particular manner a movement goal maybe reached may be pre-coded so that the user's input action is simply toselect the movement. That is to say, how the movement goal is reachedfollows computer coder's purpose and design (i.e., the software design),not the purpose of the user. The end use of any DAVE is tore-train/restore brain-to-extremities-communications (synonymously,commands) to impaired physical extremities in order to achievefunctional utility. Each user controls at least one virtual body partDAVE to simulate the kinds of physical movements/functions desired to bemade by the user.

ABI survivors have a major, pervasive problem, i.e. how to re-learn tocontrol disabled physical extremities before/without being able to movethem. Since survivors cannot partially or totally physically moveimpaired extremities, DAVEs represent and provide, in effect, aneuroprosthetic platform for brain exercises and games which makes itpossible to exercise the brain processes specific to motor (physical)movements. The brain, as the command and control organ of the humanbody, acquires communications links to the body exceedinglyspecifically: for example, learning to play any of Mozart's 27 pianoconcertos does nothing to execute one's tennis backhand or improve golfputting accuracy.

As a non-limiting example embodiment of the conjoining aspects of DAVEs,consider the task of opening ajar. To remove a virtual lid from avirtual jar, a user with a disabled left hand would use his unaffectedright hand to direct inputs to control the DAVE of an unaffected righthand to grasping the virtual jar and inputs to control a DAVE of thevirtual left hand (the user's affected physical hand), to twist/removethe virtual lid from the virtual jar. This simulated task could beaccomplished with any combination of directly controlled DAVEs andpre-coded DAVES. The jar opening tasks is merely exemplary; embodimentsof the methods and system described herein may include simulation of anyextremity task or movement.

In a non-limiting embodiment, conjoining interactively controlled singleor multiple DAVEs, and/or pre-coded movement, single or multiple DAVEsto simulate purposeful physical re-training movements is supported by atleast the following:

learning/training to make purposeful physical movements requirespersonal, brain-to-extremities (including core body) processes;

no one can physically train for the impaired patient;

movement is idiosyncratic notwithstanding the goals of movements beinguniversal (e.g., walking is universal, each person's walk isdistinctive);

if one suffers an ABI or is otherwise brain-to body-affected-impaired,physical movements are, figuratively, brain-to-disabled extremity(ies)which are “off-line”, the damaged brain no longer communicates as it didto the extremities pre-injury;

users must re-train (by definition, idiosyncratically to move i.e. tocontrol extremities);

no one can virtually, physically re-train for the impaired patient;

movement-impaired individuals can be assisted, receive therapy andengage in rehabilitation, i.e. to re-train to move extremities theycannot move; and

PEGs/DAVEs are an effective re-training may be to move track/mimic anoriginal training to move, i.e. particular brain-to-extremitiesprocesses.

ABI survivors (synonymously users) who cannot move extremities andchoose to use PEGs/DAVE retraining will control virtual images as closeas possible to physical and/or occupational brain-to-impaired-extremityrehabilitation processes. In an aspect, DAVEs may be constructed bystoring user anatomical and physiological data in a database; andcreating user-controllable/directed DAVE images based on a body modelderived from the users' anatomical and physiological data or by usinggeneric body models. In this manner, a DAVE may be customizable to auser. DAVEs may also be computer pre-programmed so that, by non-limitingexample, any user's inputs result in simulated physical movement, orseries or movements, by either or both virtual affected or unaffectedhands.

DAVEs may be constructed as specialized computer digital multimediapackages capable of receiving and processing digital inputs andgenerating visual and/or audio outputs for display and/or presentationto a user via a digital device. In some embodiments, the user maycustomize for or a DAVE's multimedia output, such as audio or visualpreferences.

The described embodiments operate in a different combination of virtualand physical environments in that they enables communications from eachsurvivor's control of DAVEs (in the play of PEGs) through a digital orother device to a body part device 128, which in a non-limiting examplemay be a physical exoskeleton, a powered orthotic device, a glove,and/or another complex multi-point interface (etc.), placed on (i.e.connected, affixed, attached and so forth to) a survivor's affected bodypart. In an aspect, the body part device exoskeleton is on the body partcorresponding to the particular DAVE(s) being controlled by thesurvivor. As the DAVEs are survivor-controlled, the exoskeleton (etc.)device may be activated to physically manipulate each survivor'saffected body part, thereby producing self-administeredphysical/occupational therapeutic manipulations to the survivor'saffected body part. DAVEs may be used, for non-limiting example, withany prosthetic, orthotic and/or any motile instrument, device and thelike.

Turning now to the drawings, FIGS. 20-23 illustrate one exampleembodiment of a retraining system that can utilize DAVEs as the virtualbody image of PEGs. FIGS. 20-23 in combination with FIGS. 1 and 2,illustrate one embodiment of a system 100 employing DAVEs as the virtualbody part displayed in PEGs. In one embodiment, a DAVE 2000 isillustrated in combination with output to a user worn output device,such as body part device 128 illustrated as a glove, which can providephysical stimulation to the user 120 (such as movement or vibration)simultaneously with the DAVE display of the user's affected extremity ortarget body part 150.

FIGS. 20-23 each illustrates a user 120 interacting with training system100. Training system 100 includes computer device 102, input device 104,and display device 106. Computer device 102 includes memory 118 (notshown) having instructions stored therein for the execution of one ormore Pre-Action Exercise Games (“PEGs”). PEGs provide ABI/TBI survivorswith brain stimulating substitutes for actual physical-action feedback.PEGs utilize, create and display one or more controllable digitalanatomical virtual extremities (DAVEs). A DAVE is illustrated in FIG. 20as left hand image 2000 displayed on display device 106. In FIG. 20,user 120 is providing therapy to an impaired extremity or target bodypart 150 illustrated as the user's left hand. User 120 uses anunimpaired limb to manipulate input device 104 illustrated as the user'sright hand shown manipulating an input device 104. Input device 104 isillustrated as a computer mouse device, but may encompass at least anyinput device described hereinabove. In an aspect, the DAVEs may beconstructed by storing, in memory 222 a user's anatomical andphysiological data in a database; and creatinguser-controllable/directed DAVE images based on a body model derivedfrom the users' anatomical and physiological data. Alternatively, a DAVEmay be constructed using generic body part models stored in memory 224.Any DAVE constructed based upon stored generic body part modes may befurther customized to a user based upon the users' anatomical andphysiological data. In this manner, a DAVE may be customizable to a user120 and realistically reflect target body part 150.

As illustrated in FIGS. 20-23, both a survivor's (i.e., user 120)physical impaired left hand (i.e., target body part 150) and a DAVE lefthand (i.e., virtual image 2000) controllable by the survivor to simulatethe survivor's desired purposeful movements where DAVEs are generated bya specially programmed controller, processor, or computer (i.e.,computer 102), and displayed to the survivor/user on a visual displaydevice (i.e., display screen 106.) The computer device 102 also isarranged to receive input from a survivor/user via, for example, a mouse(i.e., input device 104, or keyboard input, or survivor brain-computerinterface signals (not shown) and utilize these input signals to controlor affect changes in the displayed DAVE characteristics.

As also illustrated in FIGS. 20-23, user 120's physical impaired lefthand (i.e., target body part 150) is illustrated, in an aspect, asattached to body part device 128. In an aspect, body part device 128 maybe, but is not limited to being, output devices such as a robotic arm,shoulder, or other limb, a prosthetic limb, a user worn device such asan exoskeleton, a powered orthotic device, or a glove, sleeve, or sock,or the like. Regardless of form, body part device 128 may include motormeans allowing articulable mechanical motion which reflects orcorresponds to DAVE motion. Body part device 128 may also include meansallowing receipt and processing of signals 132 (FIG. 1) from computerdevice 102. Signals 132 may cause the external body part device 128 tomove by controlling the motor means move the body part devicesubstantially in unison with the movement action of the DAVEconcurrently displayed on display device 106.

In some examples, the external body part device 128 may stand alone andbe placed in a location viewable by the user 120. When body part device128 is not attached to user 120, the body part device can serve as anadditional output display. When utilized as an additional outputdisplay, the mechanical motion of the body part device directed bycontrol signals allowing the user to visualize a three-dimensionalphysical motion of the DAVE displayed motion.

When body part device 128 is attached to a user's target body part 150,the body part device motion provides actual physical actions andmovement to the user's impaired extremity or target body part 150, sothat the user receives feedback via sensory-action return signals fromthe training system 100. In this manner, the methods and systemdescribed herein may provide a combination of cognitive pre-actiontraining and impaired extremity movement training contemporaneously.

In an additional or alternative aspect, body part device 128 may beconfigured to receive one or more control signals from computer device102, as described above in relation to FIG. 2, corresponding to thevirtual movement of the virtual body part or DAVE being manipulated byuser 120. Based on the one or more control signals, the body part device128 may process the control signals and may stimulate one or more targetbody parts 150 of the user 120 (or of a non-user (not shown)) to promptmovement of one or more body parts, which may include target body part150.

In the aspect illustrated in FIGS. 20-23, body part device 128 isembodied as a glove device (not separately shown). A glove device foruse with system 100 as body part device 128 includes one or more digitalstepper motors that may receive signals generated by computer 102 thatreflect user-directed DAVE motion and translated into motor controlsignals. In an aspect, the motors may be attached to or embedded withinthe glove device. In an aspect, the motors may control wires attached toor embedded in the glove device to contract or extend in an articulablemanner that contracts or extends finger portions of the glove. In thismanner, the glove device may contract or extend, selectively, one ormore of the glove fingers enabling the glove device to move the user'simpaired hand to a variety of positions. The glove device may beconstructed from any soft flexible fabric or material, includingadditive manufacturing materials (i.e., 3 dimensional printedmaterials), or any combination of materials. In one aspect, the glovedevice may include reinforced materials, such as plastics or rubbers, innon-articulating areas such as the palm, finger lengths, or finger tips,combined with softer materials in areas of articulating joints. Glovedevice may also include one or more sensing devices for sensingpositioning and motion, and include a transmission means forcommunicating positioning signals to computer device 102. Alternatively,or in addition, glove device may include one or more electrode devices,such as transdermal electrodes or other neuro-stimulation electrodes,for additional electrostimulation of a user's target body part 150. Inthis aspect, target body part stimulation signals may be communicated bycomputer 102 in addition to movement signals so that body part devicemay additionally or alternatively provide electrostimulation therapy.

Operation of the aspect illustrated in FIGS. 20-23 will now bedescribed. In FIG. 20, system 100 is initialized to select and load theappropriate PEGs and to display either a default or user customized DAVEto user 120. As illustrated, user 120 initiates therapy to an impairedleft hand as the target body part 150. Body part device 128, a therapyglove as described above, is securely attached to the user's target bodypart 150. User 120 utilizes a non-impaired body part to manipulate aninput device 104, illustrated as the user's right hand manipulating acomputer mouse. DAVE 2000 visually simulates an aspect of theuser/survivor's left hand physical movement and as illustrated, DAVE2000 exhibits an open left hand arrangement.

In FIG. 20, as the user manipulates input device 104 to controlillustrated DAVE 2000 displayed on display 106, user 120 creates motioninputs or physical inputs 122 (FIG. 1) into input device 104. Physicalinputs 122 are processed and forwarded to computer device 102 as inputsignals 110 (FIG. 1) and represented by the arrow 110 in FIG. 20.

In FIG. 21, computer device 102 has received user input signals 110 andprocessed the user's input signals to reflect signal 114 (FIG. 1) outputto the display device 106 and illustrated in FIG. 21 as arrow 114. InFIG. 21, display device 106 now shows DAVE 2100 in a differentconfiguration. DAVE 2100 exhibits a closed left hand or fistarrangement.

In FIG. 22, computer device 102 transmits signal 132 (FIG. 1),illustrated in FIG. 22 as arrow 132, to body part device 128 forcontrolling body part device 128. Signal 132 is transmitted concurrentlyor substantially simultaneously with the device 106 displaying the DAVE2100 simulated left hand physical movement, the computer device 102 alsotransmits signals, by electrical signal (wired or unwired), or soundcommunication, or other transmission technology, to body part device128.

FIG. 23 illustrates body part device 128 receiving signal 132 fromcomputer device 102 and performing a corresponding signal directedmovement. FIG. 23 illustrates body part device 128, embodied in FIGS.20-23 as a user worn glove, has moved from an open left hand arrangementillustrated in FIGS. 20-22 to physically move target body part 150 intoa closed left hand or fist arrangement as shown in FIG. 23.

In an aspect, display device 106 may be a digital, holographic or otherdisplay device that displays the DAVE's simulated or virtual left handphysical movement. Additionally, in an aspect left hand body part device128 may be an exoskeleton, a powered orthotic, a glove and/or othercomplex multi-point interface (collectively a “hand device” or HD) thatis physically attached or associated with the survivor/user's impairedhand. Signals 132 may direct the movement of the HD such that the HDmimics the movement or action being displayed by the DAVE. In thismanner, as the survivor-controlled DAVE hand opens and closes, the HDattached to or associated with the survivor's impaired hand alsophysically opens and closes the survivor's physical left hand (fingers,thumb and or wrist in any combination). As can be seen, as the survivorplans and executes changes to the DAVE on the display device, he isrewarded with the DAVE changing and substantially simultaneously with aphysical self-directed motion the impaired hand.

In an aspect, the computer device 102 may include a graphic userinterface which enables a user to control the on-screen DAVE.

In an aspect, DAVE control signals 110 originate with the user operatinga standard computer mouse (or any input device 104) to input signals tothe computer device 102.

In an aspect, the DAVE control signals are processed by computer device102 for display on display 106, and sent from the computer device 102 toa DATEQ™ device (not shown) or similar data acquisition circuitrycapable of providing the appropriate signal conversion from the outputof the computer device to the input of the HD. For example, if thecomputer device output is USB and the HD utilizes a serial signal input,a DATEQ™ can be utilized for signal conversion. Appropriate powersources for circuitry are available.

In an aspect, DAVE control signals utilized to drive the display deviceand concurrently or simultaneously output from the computer device tothe HD device can be sent to an ARDUINO™ circuitry board (or othersuitable circuitry board) and used to control the HD device movement viaone or more digital motors or other motion producing devices. In anaspect, one or more stepper motors such as micro stepper motors may beutilized to affect HD motion. Any suitable communications and controlsoftware enabling system component communications and control betweenthe system computer device and peripheral devices may be utilized asrequired. Further, appropriate power sources are connected to allcircuitry and motors. In an aspect, batteries or other power source maybe embedded in the HD.

Thus, in one embodiment, the computer device 102 passes signals to theHD (either through a DATEQ™ arrangement, an ARDUINO™ arrangement, (orother similar circuitry)) to open or close the user's impaired physicalhand in a manner corresponding to the user's inputs to open or close aleft hand DAVE displayed to the user. In this manner, a user of themethods and system described herein may self-administers physicalmovement therapies to one or more impaired or target body parts.

Referring now to FIG. 24, a flowchart illustrates blocks in oneembodiment of a method 2400 of pre-movement and actionself-training/self-learning. Method 2400 is discussed with additionalreference to FIGS. 1-24 above. In block 2405, system 100 is provided toa user. In one embodiment, system 100 includes a computer device 102, adisplay device 106 disposed in communication with computer device 102,and input device 104 disposed in communication with computer device 102as discussed above. In another embodiment, system 100 also includesfeedback device 130 and/or body part device 128 disposed incommunication with the computer device 102. In another embodiment,system 100 optionally includes feedback device 130.

In block 2010, system 100 displays to a user a virtual body part. In oneembodiment, the virtual body part is selectable or includes at least oneselectable body part portion shown on display device 106 in a firstposition or configuration.

In block 2415, system 100 optionally provides an instruction to the userto perform a task related to the virtual body part. In some embodiments,the instruction is self-evident, is provided in an instruction manual,is provided verbally by a therapist or other person, or is provided insome other form. In one embodiment, the task includes moving the virtualbody part in virtual 3D space, changing the position of the virtual bodypart or the at least one selectable body part portion to a secondposition in virtual 3D space, changing the configuration of the virtualbody part, moving an object in virtual 3D space, grasping a virtualobject, touching a virtual object, aligning the virtual body part with avirtual object or displayed reference point, positioning the virtualbody part relative to a virtual reference point such as a displayedtarget, using the virtual body part to select a virtual object,releasing an object, rotating at least a portion of the virtual bodypart in virtual 3D space, or selecting one object among a plurality ofdisplayed objects. In one embodiment, the task includes the useridentifying a condition to be met and/or application of a rule, wherethe user input includes or demonstrates application of the rule oridentifying the condition to be met.

In block 2420, system 100 receives one or more user inputs from theuser. The user input can include a selection input in response to theinstruction. In one embodiment, the instruction input is associated withthe virtual body part or with one or more portions of the virtual bodypart. Alternately or additionally, the user input is a movement andaction input associated with one or more portions of the virtual bodypart or with the entire virtual body part. In one embodiment, block 2420includes detecting a biomarker of the user. In one embodiment, block2420 is performed by input device 104, which may be user movement andaction recognizing component 124, described hereinabove with referenceto FIG. 1.

In one embodiment, user measurement device 108 obtains a usermeasurement or signal, such as a neurological signal of the user,measurement of a biological substance of the user, or detection of abiomarker. System 100 optionally compares the user measurement or signalto a control value.

In optional block 2425, system 100 displays to the user, in response tothe user input, some indicia 1716 associated with one or more selectableportions of the virtual body part. As discussed above, for example, withreference to FIGS. 17A and 17B, indicia 1716 includes color, shading,intensity, a marking, a symbol, or any device that communicates to theuser that a selectable portion can be selected or that a selectableportion has been selected.

In block 2430, system 100 displays to the user a movement and action ormovement of the virtual body part (or one or more portion thereof) to asecond configuration based on the user input(s). In one embodiment, theuser input(s) is (are) at least a part of pre-movement and pre-actionself re-training/re-learning by the user to make physical movements.

In one embodiment, method 2400 includes block 2435 of system 100outputting a control signal to a tangible body part device 128. Here,block 2405 includes providing a system having the body part device 128disposed in communication with computer device 102. As discussed above,examples of body part device 128 include an output devices such as aprosthetic limb or body part, a robotic device, powered orthotic device,or other tangible and operable device. In one embodiment, the body partdevice 128 is operationally connected to the user. In anotherembodiment, the body part device 128 is not connected to the user, suchas a prosthetic or robotic device positioned adjacent system 100.

When system 100 includes feedback device 130, method 2400 optionallyincludes block 2440 of providing feedback to the user. In oneembodiment, the feedback is an electrical signal configured to stimulatea muscle or nerve of the user (e.g., a neurological signal), tactilefeedback (e.g., via a haptic device), visual feedback, demonstrativefeedback (e.g., demonstrated movement and action using a virtual bodypart or a tangible body part device), audio feedback, or an electricalsignal configured to control a tangible body part device disposed incommunication with system 100. When the feedback is an electrical signalconfigured to control a tangible body part device, the body part devicepreferably is connected to the user. In one embodiment, the electricalsignal contemporaneously causes the tangible body part device tosubstantially perform the movement and action performed by the virtualbody part.

In one embodiment, method 2400 optionally includes blocks 2445-2455. Inblock 2445, system 100 displays a demonstrative movement and action ofthe virtual body part. For example, system 100 shows a virtual body partmoving a hand from an open position to a closed position.

In block 2450, system 100 indicates to the user one or more portion ofthe virtual body part that is used to perform the demonstrative movementand action. For example, system 100 displays in a different color themuscle(s) or muscle group(s) used by the virtual body part to open andclose the hand. In block 2450, system instructing the user to mimic thedemonstrative movement and action. The instruction may be presented tothe user by an on-screen message, audible command, or other means ofcommunication.

In block 2455, in response to instructing the user to mimic thedemonstrative movement and action, system 100 receives a user inputcorresponding to the portion(s) of the virtual body part used to performthe demonstrative movement and action. For example, the user selects themuscle group used to close the hand. In response to the user input,system 100 displays the demonstrative movement and action.

Examples, as described herein, may include, or may operate on, logic ora number of modules or mechanisms. Modules are tangible entities capableof performing specified operations and may be configured or arranged ina certain manner. In an example, circuits may be arranged (e.g.,internally or with respect to external entities such as other circuits)in a specified manner as a module. In an example, the whole or part ofone or more computer systems (e.g., a standalone, client or servercomputer system) or one or more hardware processors may be configured byfirmware or software (e.g., instructions, an application portion, or anapplication) as a module that operates to perform specified operations.In an example, the software may reside (1) on a non-transitorymachine-readable medium or (2) in a transmission signal. In an example,the software, when executed by the underlying hardware of the module,causes the hardware to perform the specified operations.

Accordingly, the term “module” is understood to encompass a tangibleentity, be that an entity that is physically constructed, specificallyconfigured (e.g., hardwired), or temporarily (e.g., transitorily)configured (e.g., programmed) to operate in a specified manner or toperform part or all of any operation described herein. Consideringexamples in which modules are temporarily configured, one instantiationof a module may not exist simultaneously with another instantiation ofthe same or different module. For example, where the modules comprise ageneral-purpose hardware processor configured using software, thegeneral-purpose hardware processor may be configured as respectivedifferent modules at different times. Accordingly, software mayconfigure a hardware processor, for example, to constitute a particularmodule at one instance of time and to constitute a different module at adifferent instance of time.

Examples, as described herein, may include, or may operate on, logic ora number of modules, modules, or mechanisms. Modules are tangibleentities capable of performing specified operations and may beconfigured or arranged in a certain manner. In an example, circuits maybe arranged (e.g., internally or with respect to external entities suchas other circuits) in a specified manner as a module. In an example, thewhole or part of one or more computer systems (e.g., a standalone,client or server computer system) or one or more hardware processors maybe configured by firmware or software (e.g., instructions, anapplication portion, or an application) as a module that operates toperform specified operations. In an example, the software may reside (1)on a non-transitory machine-readable medium or (2) in a transmissionsignal. In an example, the software, when executed by the underlyinghardware of the module, causes the hardware to perform the specifiedoperations.

Accordingly, the terms “module” and “module” are understood to encompassa tangible entity, be that an entity that is physically constructed,specifically configured (e.g., hardwired), or temporarily (e.g.,transitorily) configured (e.g., programmed) to operate in a specifiedmanner or to perform part or all of any operation described herein.Considering examples in which modules are temporarily configured, oneinstantiation of a module may not exist simultaneously with anotherinstantiation of the same or different module. For example, where themodules comprise a general-purpose hardware processor configured usingsoftware, the general-purpose hardware processor may be configured asrespective different modules at different times. Accordingly, softwaremay configure a hardware processor, for example, to constitute aparticular module at one instance of time and to constitute a differentmodule at a different instance of time.

Additional examples of the presently described method, system, anddevice embodiments include the following, non-limiting configurations.Each of the following non-limiting examples may stand on its own or maybe combined in any permutation or combination with any one or more ofthe other examples provided below or throughout the present disclosure.The preceding description and the drawings sufficiently illustratespecific embodiments to enable those skilled in the art to practicethem. Other embodiments may incorporate structural, logical, electrical,process, and other changes. Portions and features of some embodimentsmay be included in, or substituted for, those of other embodiments.

As used in this disclosure, the terms “component,” “module,” “system”and the like are intended to include a computer-related entity, such asbut not limited to hardware, firmware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a computing device and the computing device can be a component. Oneor more components can reside within a process and/or thread ofexecution and a component may be localized on one computer and/ordistributed between two or more computers. In addition, these componentscan execute from various computer readable media having various datastructures stored thereon. The components may communicate by way oflocal and/or remote processes such as in accordance with a signal havingone or more data packets, such as data from one component interactingwith another component in a local system, distributed system, and/oracross a network such as the Internet with other systems by way of thesignal.

Moreover, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom the context, the phrase “X employs A or B” is intended to mean anyof the natural inclusive permutations. That is, the phrase “X employs Aor B” is satisfied by any of the following instances: X employs A; Xemploys B; or X employs both A and B. In addition, the articles “a” and“an” as used in this disclosure and the appended claims should generallybe construed to mean “one or more” unless specified otherwise or clearfrom the context to be directed to a singular form.

Various aspects or features will be presented in terms of systems thatmay include a number of devices, components, modules, and the like. Itis to be understood and appreciated that the various systems may includeadditional devices, components, modules, etc. and/or may not include allof the devices, components, modules etc. discussed in connection withthe figures. A combination of these approaches may also be used.

The various illustrative logics, logical blocks, modules, and circuitsdescribed in connection with the embodiments disclosed herein may beimplemented or performed with a general purpose processor, a digitalsignal processor (DSP), an application specific integrated circuit(ASIC), a field programmable gate array (FPGA) or other programmablelogic device, discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the processesdescribed herein. A general-purpose processor may be a microprocessor,but, in the alternative, the processor may be any conventionalprocessor, controller, microcontroller, or state machine. A processormay also be implemented as a combination of computing devices, e.g., acombination of a DSP and a microprocessor, a plurality ofmicroprocessors, one or more microprocessors in conjunction with a DSPcore, or any other such configuration. Additionally, at least oneprocessor may comprise one or more modules operable to perform one ormore of the steps and/or actions described above.

Further, the steps and/or actions of a method or algorithm described inconnection with the aspects disclosed herein may be embodied directly inhardware, in a software module executed by a processor, or in acombination of the two. A software module may reside in RAM memory,flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a harddisk, a removable disk, a CD-ROM, or any other form of storage mediumknown in the art. An exemplary storage medium may be coupled to theprocessor, such that the processor can read information from, and writeinformation to, the storage medium. In the alternative, the storagemedium may be integral to the processor. Further, in some aspects, theprocessor and the storage medium may reside in an ASIC. Additionally,the ASIC may reside in a user terminal. In the alternative, theprocessor and the storage medium may reside as discrete components in auser terminal. Additionally, in some aspects, the steps and/or actionsof a method or algorithm may reside as one or any combination or set ofcodes and/or instructions on a machine readable medium and/or computerreadable medium, which may be incorporated into a computer programproduct.

A number of embodiments of the methods, and system herein have beendescribed. Various modifications may be made without departing from thespirit and scope of the disclosure. For example, various forms of theflows shown above may be used, with steps re-ordered, added, or removed.Accordingly, other embodiments are within the scope of the followingclaims.

We claim:
 1. A method for improving performance of physical actions of auser with an affected brain comprising: providing an apparatus to theuser having one or more self-teaching virtual training games storedtherein that, upon execution, simulate at least one physical actionusing one or more controllable digital anatomical virtual extremities;creating the one or more digital anatomical virtual extremities; eachsaid digital anatomical virtual extremity being configured to the userby storing measured user anatomical data and measured user physiologicaldata in a database and creating an extremity model based on a model dataderived from said anatomical and physiological data; constructing one ormore pre-coded digital anatomical virtual extremities having a series ofpre-determined movement actions; displaying on a display device the oneor more digital anatomical virtual extremities; displaying on thedisplay device the one or more pre-coded digital anatomical virtualextremities; receiving, from an input device controlled by the user,inputs that control the simulated physical action of the one or moredigital anatomical virtual extremities generated by the apparatusconjoined with one or more of the pre-coded digital anatomical virtualextremities generated by the apparatus; wherein the user inputscontrolling the user-controllable image instantiate the kinetic imageryof the simulated physical action of the user; and wherein theinstantiation of kinetic imagery of the simulated physical action andfeedback to the user based on the simulated physical action of the usercontrollable image and pre-programmed image are associated withimproving performance of the physical action of the user; providing anoutput device attached to a user's affected physical extremity, andwherein upon motion of the digital anatomical virtual extremityrepresenting a user's affected extremity on the display, a signal issimultaneously transferred to the output device resulting in physicalstimulation of the affected physical extremity.
 2. The method of claim 1wherein providing to the user on an apparatus one or more self-teachingvirtual training games that simulate at least one physical action usingone or more pre-coded digital anatomical virtual extremities.
 3. Themethod of claim 1 wherein the input device is a computer mouse, a touchscreen, a device configured to measure user head movements, a deviceconfigured to measure user eye movements, a brain-computer interface, ora wired communications device or wireless communications device.
 4. Themethod of claim 1, wherein the digital anatomical virtual extremitiescomprise virtual body parts exhibiting analogous true range of motion tosimulate physical movements.
 5. The method of claim 1, whereinconstructing and creating the one or more digital anatomical virtualextremities configured to the user by: storing anatomical andphysiological data in a database; and calculating a user model based ona generic body model derived from anatomical and physiological data. 6.The method of claim 1 wherein the output device is an articulablephysical extremity model having attachment means for allowing the user'simpaired extremity to be securely attached thereto.
 7. The method ofclaim 1 wherein the output device is an extremity exoskeleton havingmotion controllable actuators.
 8. The method of claim 1 wherein theoutput device is a motion controlled glove.